Shadowing Practice: Maybe we were wrong - Learn English Speaking with Video
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278 משפטים
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The last couple years of being a developer has been,
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you know, I guess kind of interesting, right?
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Fellas, I actually have some good news here, okay?
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Things have been changing.
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Some whispers have been halving and new news is hitting the front lines.
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It turns out being a software developer might actually be pretty dang awesome.
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Now, if you haven't been in the software development realm for the last three years,
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let me do a quick recap for you.
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First off, you shouldn't teach your kids to code because honestly,
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you should let AI do
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that says ai salesman number one you've said ai could wipe out half of all entry-level white-collar jobs
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and spike unemployment to 10 to 20 percent in the next one to five years yes
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and of course dario here always just giving it to you
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straight by the way look at how happy he is he
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is answering this question with such alacrity he has never been
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more excited to tell you you are about to lose your
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job than i've seen any man on earth this guy loves
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firing people he loves firing people not even from his own company and
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if that's not enough for you of course last year we
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had sam altman sam gyppity altman just dropping the death star
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the day before big product announcements just letting everybody know hey what we're about to do it's pretty big
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and of course this is a very confusing message is he saying he's the bad guys is
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that what he's saying is does he release the death star
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i'm still confused to this like this post actually eats like
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it's an earworm okay it eats me from the inside like
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what the hell happened here why why why would you post this
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but the thing i wanted to to talk about this this
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turning point that's happening is this right here look at this
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just in sam altman says ai probably won't trigger the job apocalypse he once predicted not only
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that but uber coo now says hey
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when you're spending a whole bunch of tokens honestly can't really tie it to features
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so there's something just kind of happening in our world there's
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some maybe some news realizing how important it is to have competent
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and good developers it's like the timeline is almost kind of oddly healing in a way.
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So we, of course, we absolutely have to go over this.
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I got a lot of yeah.
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Okay.
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The vindication gap is going to land on this video,
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but more importantly, I want to do a quick thank you to the sponsors.
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Hey, is that HTTP?
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Get that out of here.
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That's not how we order coffee.
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We order coffee via SSH terminal.shop.
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Yeah.
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You want a real experience.
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You want real coffee.
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You want awesome subscriptions.
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So you never have to remember again.
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Oh, you want exclusive blends with exclusive coffee and exclusive content then check out cron you don't know what ssh is
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well maybe the coffee is not for you
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okay first let's talk about sammy jippity altman right here saying
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hey maybe he was wrong here's kind of exactly what he
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said this of course is from a commonwealth bank of australia
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conference in sydney just last tuesday it says this i don't think we're gonna have the kind of jobs apocalypse
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that some of the companies in our space advocate
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or talk about by the way i love the fact
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that he says advocate like there's actual companies in his space
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advocating for everybody to lose their jobs you know who we're
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talking about okay you know who sammy boy's talking about he's
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not talking about you know minstrel ai the bro's talking about anthropic he's just like yo anthropic
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they really want you to lose the jobs here it could
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also be to be fair this could also be some sort
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of jab at musk as well i can't really tell
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but either way very hilarious i thought there was going to
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be more impact on entry-level white-collar jobs being eliminated by now
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than has actually happened i now think i understand more about why it hasn't
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and i'm obviously grateful but
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that is an area where my intuitions were just off we
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really do care about our interactions with people he added
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which he said for better or for worse updated me to thinking
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that the jobs picture is likely going to be very different
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than we thought okay whoopsie poopsie turns out maybe people like to talk to people
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and interact with people
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and building great products actually turns out maybe just might take people might take people to do
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that huh crazy i i just thought we were gonna get
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metered intelligence i thought i thought you stole the internet took
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everything compressed it down into the sweet next token prediction
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and then sell us back to us and then we pay for it
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and it's just like that
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and that's how the world works of course sam's actually not
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the only one goldman sachs ceo david m solomon says
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that ai won't eliminate 25 of the jobs he's just saying
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hey it turns out people will spend their time in more productive ways
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and he makes some cases down here saying hey did like any other technology ever do this
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and what we're observing is not true in the data
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so this is actually kind of a positive development i'm actually
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pretty excited about this i would love to see things actually
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healing from this craze where you have all these ceos
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that have been told for the last two years of these
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companies like no bro bro i'm just letting you know you
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gotta just like dude just like fire everybody you don't need them
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because you got ass dude you got open claw open claw
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is gonna do everything you just say yo million dollar sass no mistakes
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and bam in just a few minutes crunching some clod four points actually 4.6 4.7 is kind of
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you're gonna have yourself a million dollar sass.
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I am so happy that this is starting to crumble
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because this is something that has needed to crumble now for a while because it is ridiculous.
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There is so many people right now that at their jobs are being forced to like a certain level of AI output.
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And if they don't make it,
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they're like heads on the chopping block,
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even if it's not a good idea.
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Like they don't even get the option of going,
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hey, is this good or bad?
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It's like, no, use it or that's bad.
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Like if you don't use it, that's bad.
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I was like, well, maybe it's not always the best thing.
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And where this is really starting to show is this right here,
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this Uber COO saying
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that heavy AI spend is actually getting harder to justify as higher token usage fails to show clear payoff in consumer features.
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Now, this of course is a headlining item.
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So let's actually watch the video as opposed to,
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you know, seeing what Twitter has to say.
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Let's look at the actual video.
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Let's hear what he has to say.
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I know, novel concept, right?
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You make your head explode, right?
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When you hear companies talking about,
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hey, 25% of code commits over the last quarter were AI driven.
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Or, you know, our token usage went from X to Y or percentage of employees,
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you know, all these sort of numbers. And it's amazing.
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And I think it's like this massive transformation of society.
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But then you sometimes go and you talk to your senior engineering leaders and you're saying,
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okay, How many projects that were on the cutting room floor got moved above the line because of the,
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you know, productivity gains because 25% of our code commits were via cloud code last, last quarter.
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That link is not there yet.
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Right?
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Like you're not, I mean,
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I think maybe implicitly there there's more that is getting shipped,
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but it's, it's, it's very hard to draw a line between one of those stats and okay,
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now we're actually producing like 24,
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5% more useful consumer features.
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And this is the COO of Uber.
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Like this guy has fully committed to this AI kind of adventure.
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In fact, they spent within the first four months,
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their operating year budget for AI.
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Like these people were committed.
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And now after all this,
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they're like, okay, wait, wait, wait, wait, wait.
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Maybe not everything that glitters is gold.
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Perhaps there are some things that we don't really see.
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These implicit features that he was talking about.
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Maybe there's more bug fixes,
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which I'm a little bit dubious on that one.
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But nonetheless, like maybe things have been changing a little bit and now we are shipping a bit faster,
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but there's no material impact.
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What we thought would be these huge,
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gigantic windfalls are, in fact,
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just not showing up in the actual data.
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And this, of course, gets me to the linear CEO post,
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which I really think just nails this whole thing,
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which is we keep hearing about the 10x or the 100x productivity gains in engineering and knowledge work.
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But outside of Model Labs,
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I haven't seen the corresponding 10x to 100x revenue growth across the market or increase in quality.
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Where is the productivity going?
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This is so good because you know where the productivity is going.
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All these people talking about this just incredible increase in productivity,
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what they're really saying?
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They're like, dude, bro, I've just set up the greatest harness ever.
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Oh my gosh, you will not believe how many different versions of Cloud Code I have running.
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Like I got G stack on top of the P stack.
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I got all the stacks going so hard.
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I got TRT coming in hot.
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Like, we're doing everything.
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I'm gonna make the most crazy commits ever.
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Like, I've just spent the last three months sharpening the sword.
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Honestly, it reminds me a lot of NeoVim config enthusiasts.
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Now, remember, back in the day,
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maybe like a year ago to five years ago,
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maybe this guy got made fun of a lot.
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You know why he got made fun of?
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Because, oh, I was always playing around with my NeoVim config.
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I wanted the perfect experience,
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and everyone was like, how could you do that?
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Now, what's, it's, I swear today is just the same story again,
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which is, oh, you know what we really need?
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We need to make the greatest agent harness.
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Like that's what we're actually missing, bro.
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Bro, it's just one more harness and then we'll actually be able to write infinite,
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free, high quality code forever.
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It'll be so fast.
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It'll be so amazing.
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Just one more harness, bro, bro.
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It's just like, I'm almost there.
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My system prompt is like 98%.
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It's just so close.
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Also, I do love the,
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like this line right here,
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because if you really think about what he's saying is,
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hey, it's all the labs.
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They're making like 10 to 100 X more money.
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Where's everybody else's money from all these AI productivity gains, huh?
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Because if everybody really is 10 to 100x more productive,
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wouldn't that show up in a bunch more revenue?
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Kind of crazy that the only people making money are the people selling shovels, huh?
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I mean, they are seeing 10 to 100x revenue.
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Jeez, that seems a little strange, isn't it?
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See, the thing that I think people are missing about this whole AI craze and all that is that,
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sure, there's a bunch of people that go zero to one with AI,
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and they're like, whoa, bro,
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this is the coolest thing ever.
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But there's a bunch of us who want to go,
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say, from 30 to 60, right?
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We're actually in the further part of the project.
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And so what I end up personally doing,
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which is something I do right here,
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is I go off and I talk about everything I want to build to the AI.
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And then I have it implement a bunch of different versions of it.
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And I go, okay, well,
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what if we change this?
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How about we put all the responsibility over here?
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And I can see like five different versions of the exact same thing go, huh?
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Okay, I like this.
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Yeah, I like that.
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Okay, I like this, like,
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it is demonstrably helping me see a bunch of different versions to really understand what makes a good interface,
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but it's not this like 100x improvement.
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I'm not even sure if I'm actually improving the speed in which I'm actually making these features.
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Maybe my understanding is a bit faster.
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Maybe the ideas I'm coming up with are a little bit more solidified.
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But maybe also, just sitting down with a pen
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and piece of paper and drawing out my ideas would have made the exact same impact.
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See, the thing that I think most people are missing people that actually instead building say the zero to one projects, right?
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There's a whole bunch of like flashy kind of shallow projects that people make.
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And they're like, see, yo,
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bro, this is so fantastic.
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No, like trying to make deep,
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integrated products that actually take a long time to think about
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and actually take a long time to come up with good ideas.
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When you use AI, it increasingly makes things more brittle and more difficult.
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No matter what you're doing,
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you have to take a step back and actually work through the problems yourself.
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And this is one thing that I've really appreciated about AI,
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I can come up with an idea,
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I can kind of type out what it should be.
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And then I can say,
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hey, go build me a mock version,
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I can look at the mock version,
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go, okay, yeah, I hate all these parts.
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This is just going to be a nightmare to maintain,
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this is going to be a source of bugs, let's change things up.
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How about you do it this way?
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Then I can look at it again,
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okay, I actually really like how this is looking,
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but I would really like this thing moved over here,
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I'd like this, and then look at it again.
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And so you can see this right here.
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This is me working through how would animations look in an immediate mode UI?
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Well, now I've had three swings at it and I go,
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okay, I actually really like this.
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This actually looks pretty good.
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Now I get to implement the thing.
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And this is what I think we're seeing is that
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when you really use this as a means to actually help you build real software,
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there's still just so much decision making and time spent thinking about how things should actually look that yeah,
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exploration is cheaper than it's ever been before,
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but actual implementation still feels really heavy.
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And if anything, making good decisions now almost feels harder,
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because of how fast you can move.
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Anywho, I just wanted to talk about this for a little bit,
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because I feel like there's just there's so much in our kind of world right now that's it's doom and gloom.
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Or it's just absolute hyping.
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It's like no AI is the worst thing.
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No, that's clear.
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Clearly, that's not real.
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Or B, it's like AI is the greatest thing that has ever existed.
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Also clearly not real.
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Like yes, it is absolutely magic.
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You can describe with practically broken English and have something come out that approximately looks like what you're describing.
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Like honestly, truly, that is a magical human feat.
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I hope that I never stopped being amazed by that because honestly, that's wild.
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You could never have convinced me six years ago,
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like that was going to happen in my immediate future.
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It's just one of the yap about something maybe a bit more positive that,
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hey, actually, I think a lot of good things are still ahead of us.
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I still think we got a lot of good time.
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And I still think competency is actually extremely important in learning how to program and being a good programmer is still,
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in fact, really important.
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Hey, the name is the Primogen.
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אוצר מילים והערות הגייה לשיעור הזה
שיעור הדיבור הזה ברמה B2 מבוסס על הסרטון “Maybe we were wrong”. בסרטון הזה יש 278 משפטים ו-2730 מילים לתרגול Shadowing. הדיבור נמשך 13:30. הדובר מדבר מהר, כ-202 מילים בדקה, אז צפו לצלילים מחוברים ומקוצרים. 85% מהמילים נמצאות בין 3,000 המילים הנפוצות ביותר באנגלית; כדאי ללמוד את השאר לפני שמתחילים.
אוצר מילים מרכזי בסרטון הזה
15 המילים המתקדמות ביותר בסרטון, עם ההגייה והמשמעות שלהן:
| מילה | הגייה | משמעות |
|---|---|---|
| harness פועל | /ˈhɑɹ.nəs/ | רָתַם |
| token שם עצם | /ˈtoʊkən/ | אֲסִימוֹן, זִ׳יטוֹן |
| stack שם עצם | /stæk/ | ערמה |
| developer שם עצם | /dɪˈvɛləpɚ/ | מְפַתֵּחַ |
| craze שם עצם | /kɹeɪz/ | שיגעון |
| crumble פועל | /ˈkɹʌmbəl/ | התפרק, התפורר |
| claw שם עצם | /klɔ/ | טוֹפֶר, טֹפֶר |
| apocalypse שם עצם | /əˈpɑkəlɪps/ | אחרית הימים, אַפּוֹקַלִיפְּסָה |
| mock פועל | /mɑk/ | סנט |
| collar שם עצם | /ˈkɑlɚ/ | צווארון |
| heal פועל | /ˈhiːl/ | שיפר \ שִׁפֵּר |
| implement פועל | /ˈɪmpləmənt/ | יישם, מימש |
| shovel שם עצם | /ˈʃʌv.əl/ | אֵת |
| correspond פועל | /ˌkoɹəˈspɑnd/ | הִתְכַּתֵּב |
| programmer שם עצם | /ˈpɹoʊɡɹæmɚ/ | מְתַכְנֵת, תׇּכְנִיתָן |
Phrasal verbs שתשמעו
| מילה | הגייה | משמעות |
|---|---|---|
| check out פועל | בדק | |
| come out פועל | /ˌkʌm ˈaʊt/ | יָצָא |
משפטים שכדאי לחזור עליהם
משפטים קצרים ושלמים מהסרטון שאפשר להשתמש בהם בשיחה יומיומית:
- That's not how we order coffee.
- Let's look at the actual video.
- You know why he got made fun of?
- How about we put all the responsibility over here?
- How about you do it this way?
דקדוק בסרטון הזה
המבנים שהדובר משתמש בהם הכי הרבה, עם המילים המדויקות מהסרטון:
| מבנה | בסרטון |
|---|---|
| הווה מושלם ממושך (Present perfect continuous) have/has been + -ing — פעולה שהתחילה בעבר ועדיין נמשכת עכשיו | have been changing · have been halving |
| הווה מושלם (Present perfect) have/has + past participle — פעולה שקרתה בעבר ועדיין יש לה חשיבות או השפעה עכשיו | has been · haven't been · you've said |
| סביל (Passive voice) be + past participle — הדגש הוא על מה שקורה, לא על מי שעושה את הפעולה | being eliminated · have been told · being forced |
הגייה ששווה לשים לב אליה
הדובר משתמש ב-66 קיצורים וצורות מקוצרות, כמו I'm, we're, don't. אמרו אותם בצורה הקצרה, כפי שאתם שומעים אותם.
- הצלילים של “th”: anthropic /ænˈθɹɒp.ɪk/, enthusiast /ɪnˈθuːziˌæst/, nonetheless /ˌnʌnðəˈlɛs/
- הצלילים של “sh” ו-“zh”: flashy /ˈflæʃi/, sharpen /ˈʃɑɹpən/, shovel /ˈʃʌv.əl/, vindication /ˌvɪndəˈkeɪʃən/, intuition /ˌɪn.tjuːˈɪʃ.ən/
- מילים ארוכות — שימו לב להטעמה: productivity /ˌpɹɒdʌkˈtɪvəti/, developer /dɪˈvɛləpɚ/, apocalypse /əˈpɑkəlɪps/, eliminate /ɪˈlɪm.ɪ.neɪt/, competency /ˈkɑm.pə.tən.si/
צלילים שדוברי עברית מתקשים בהם:
- /w/ — שפתיים מעוגלות, לא /v/: earworm /ˈɪ(ə)ɹˌwɚm/, windfall /ˈwɪnd.fɔːl/, whisper /ˈ(h)wɪspɚ/, whoa /woʊ/, wipe /waɪp/
- /æ/ — פתוח יותר מה-“אֶ” העברית, לא כמו “a” ב-“cup”: stack /stæk/, anthropic /ænˈθɹɒp.ɪk/, sass /sæs/, sammy /ˈsæmi/, enthusiast /ɪnˈθuːziˌæst/
- /r/ — הלשון לא נוגעת בשום מקום, לא ה-“ר” הגרונית: productivity /ˌpɹɒdʌkˈtɪvəti/, harness /ˈhɑɹ.nəs/, uber /ˈuːbəɹ/, anthropic /ænˈθɹɒp.ɪk/, craze /kɹeɪz/
איך לתרגל עם הסרטון הזה
- הקשיבו לכל הסרטון פעם אחת בלי לדבר, ורשמו את המילים שאתם לא מכירים.
- התחילו במהירות 0.75×, תרגלו Shadowing משפט אחר משפט, וחזרו למהירות רגילה כשזה מרגיש קל.
- הקליטו את עצמכם והשוו למקור, תוך תשומת לב למילים כמו harness, token, stack.
מהי טכניקת השאדואינג?
שאדואינג היא טכניקת למידת שפה מבוססת מדע שפותחה במקור להכשרת מתורגמנים מקצועיים ופופולרית על ידי הפוליגלוט ד"ר אלכסנדר ארגואלס. השיטה פשוטה אך עוצמתית: אתה מקשיב לאודיו באנגלית ילידית וחוזר עליו בקול רם מיד — כמו צל העוקב אחרי הדובר עם עיכוב של 1–2 שניות בלבד. בניגוד להאזנה פסיבית או תרגילי דקדוק, שאדואינג מכריח את המוח והשרירים בפה לעבד ולשחזר דפוסי דיבור אמיתיים בו זמנית. מחקרים מראים שזה משפר משמעותית את דיוק ההגייה, האינטונציה, הקצב, הדיבור המחובר, הבנת השמיעה ושטף הדיבור — מה שהופך אותו לאחת השיטות היעילות ביותר להכנה לIELTS Speaking ולתקשורת באנגלית בעולם האמיתי.