FREE Tutorial Prompt Engineering Terlengkap 1,5 JAM 🔥 Belajar GPT dari Dasar Sampai Mahir!

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Transcript

00:00:00Over the next hour or so, we'll be learning about Chrome Engineering.

00:00:03So this is the material that I can bring to my friends who are members of Belajar GPT,

00:00:08a platform where we learn about various kinds of AI

00:00:11and how to use it, maximize it, master it.

00:00:15Well, this is one of our flagship courses that I am sharing for free on YouTube.

00:00:21For friends here, friends can watch everything for free on my YouTube channel,

00:00:27But there are conditions. We have a gentleman's agreement, okay?

00:00:30So if you are gentle friends, or gentle woman agreement, because of emancipation.

00:00:34So if you guys feel this material is useful,

00:00:38Friends, please subscribe to my channel and comment on what we can improve in the future.

00:00:44And you can check out Learn GPT too.

00:00:46So I ask you to please just subscribe.

00:00:51More or less like that, the gentleman's agreement is only if this is beneficial.

00:00:55So okay, let's get started.

00:00:59Well, maybe I'll share a little about learning GPT first.

00:01:04What is GPT Learning? Why do we do it like this?

00:01:06So, basically it's like, we make stories, we make courses, and we make software.

00:01:13The story is content like this.

00:01:15We create courses, we actually have several courses.

00:01:17We have GPT Pro Learning which is from scratch.

00:01:21For friends who need to start from zero, the need to become an expert.

00:01:25There was an introduction course that was actually similar to today's YouTube videos.

00:01:28And there's Excel.

00:01:30And we will have several other courses in the future.

00:01:33Well, and software like that.

00:01:36So in Learning GPT, we do everything ourselves.

00:01:41So I, I happen to be the one who does everything myself.

00:01:44So I created the content, I created all the coding, I created it myself using the cloud.

00:01:51So if you guys want to know how to join us.

00:01:57But now I can really do it.

00:01:58So everyone can now make their own website.

00:02:00We even held a workshop on how ordinary people can create a landing page for an ordinary website using this game.

00:02:08But maybe there are a lot of questions like that.

00:02:10Can I really do it?

00:02:11What kind of background should I have?

00:02:13Is it suitable to study like this?

00:02:15Just happy.

00:02:15So my background is actually in marketing.

00:02:19So I'm mostly in the economics and technology industries.

00:02:26The last two big companies I worked for were ByteDance and Alibaba.

00:02:31ByteDance is TikTok, Alibaba is Lazada.

00:02:33And I have collaborated with several other big companies.

00:02:37So my background is professional.

00:02:39I happen to be in between my professional work at the office, I create content on YouTube.

00:02:46Now, it's not wrong that the subscribers are more than this.

00:02:4980 thousand, hopefully it can go even higher.

00:02:52And now I'm making this Learn GPT.

00:02:57Well, what I want to bring is that my background is not a tech person.

00:03:03I'm a marketing person.

00:03:05I was thinking about how to make it look good,

00:03:10like fun, nice to watch for the audience and so on.

00:03:16Flow, journey like that.

00:03:17But my ability to use AI can make me create a website

00:03:23and I have many other side business projects that I couldn't do without AI.

00:03:30I used to really want to start a business, I even started a startup before.

00:03:33We got funding from venture capital in Japan.

00:03:37But the business models I can create are limited.

00:03:39Why? Because I need a CTO, or chief technology officer.

00:03:43Or like I need an analyst, I need something, all sorts of things.

00:03:45With AI, the subscription price now ranges from around 20 dollars to 100 dollars.

00:03:51If I want something that's quite good, it's like I have several employees at once.

00:03:56So, originally I could have done more with my capacity as just one person.

00:04:04Like GPT, now the team has two people helping.

00:04:08So, one customer support and the other help with content.

00:04:10But, courses, coding, all that stuff is still my own.

00:04:15Go ahead.

00:04:17Okay.

00:04:19The material is about prom engineering.

00:04:22Just for friends here, maybe many of you are confused like,

00:04:25What is PROM Engineering?

00:04:26And now there is a new name called context engineering.

00:04:30What do you mean by that?

00:04:31So, prom engineering is everyone talking about prom engineering like,

00:04:35Oh, we need to make a good prom, buy prom templates and all that.

00:04:41I, I would like to argue, friends do not need to buy prom templates.

00:04:45What you need is how you can design your own prom.

00:04:51Because of the prom template, I've bought a lot of prom templates that people say are good.

00:04:57So, what's the end result?

00:04:59We have to change it ourselves, we have to edit it ourselves.

00:05:01And in the end, it now depends on how smart the AI you use is.

00:05:05If the AI is smart enough, there are tricks.

00:05:08We can ask the AI, hey, I want to do this.

00:05:11Please ask me, ABCDFG, so that later we can make a prom that we can reuse.

00:05:18So, we asked the AI to make us a prom.

00:05:20However, the development of the mind can only take place if we understand the engineering context.

00:05:26What is context engineering?

00:05:28Why is he different from prom?

00:05:29For prom, we only make it like designing the input for each output.

00:05:36So, what does that mean?

00:05:38We just write.

00:05:40In the engineering context, we really think of AI as our employees.

00:05:44Where this AI can be sort of onboarded, it understands the context of what we're doing, and all sorts of things.

00:05:57For example, like this.

00:05:58So, let's make a short analogy, okay?

00:06:01How do you onboard new employees?

00:06:05For example, if we become new employees or we have a team, we want to join our team.

00:06:10Or for example we work in groups.

00:06:12He can't do things like, eh, work, work, work like that.

00:06:16This job, this job, this job.

00:06:17You can't do that, right?

00:06:18Because I was confused, what company is this, who do I work with, where do I work, and so on.

00:06:25So, how do you onboard new employees?

00:06:30This is the stage when we recruit people.

00:06:33Not even onboarded yet, just recruiting first.

00:06:35We have to make what's it called, a job description.

00:06:38What for?

00:06:39To attract suitable candidates.

00:06:42What do you mean?

00:06:44For example, if we want to look for someone who is, let's say, a social media specialist.

00:06:49Make that, oh, can make all kinds of content.

00:06:51But now there are various kinds of specialist social media.

00:06:53There are some specifically for TikTok.

00:06:56Anyone can make carousel content.

00:07:00There are only people who are good at this on YouTube, that's all.

00:07:02For example, if I make it, I look for a team of specialists on YouTube.

00:07:06Because of ngapak-ngap, my biggest channel on YouTube.

00:07:08That's different, looking for specialist content or specialist social media.

00:07:14Because most social media specialists focus on Instagram or TikTok.

00:07:18Even Instagram and TikTok, the people are different.

00:07:20So the job description is very important to determine,

00:07:23Oh, what kind of person are we looking for?

00:07:26Okay?

00:07:27Once the job description appears, create it and we can check it.

00:07:31People are looking for it everywhere, abroad, and so on.

00:07:35Let's make this poster.

00:07:37People register, we need an interview, right?

00:07:41Interview, we ask questions like, oh, what can you do?

00:07:43What do you need? How much do you need? How much is your salary?

00:07:47All sorts of things, like that.

00:07:48I've got it, it might be long.

00:07:49Like maybe 3 interviews, 4 interviews.

00:07:53Then it was like, maybe about a month, 1.5 months.

00:07:55Until you find the right employee.

00:07:57Come in, onboarding.

00:07:58Onboarding first.

00:07:59It's impossible to just tell them to work straight away.

00:08:01What is onboarding?

00:08:02Let me tell you first, what is this company?

00:08:06What does he do?

00:08:08How many people are on the team?

00:08:11Who's in it?

00:08:13Then like, simple like for example,

00:08:15If you're at the office, where do you get food?

00:08:18Then, for example, what's my email?

00:08:22Well, it seems simple like that.

00:08:26It seems easy.

00:08:27But, we like to ignore it, you know.

00:08:31There are so many cases, especially if the message is very large.

00:08:34Where, the onboarding is not neat.

00:08:39And makes employee turnover high.

00:08:41Turnover means,

00:08:42people come in, then he comes out.

00:08:44Why?

00:08:44Because it fits perfectly.

00:08:46This work period is a lot.

00:08:48I feel like I'm not being listened to.

00:08:50I feel like this is too complex.

00:08:53This,

00:08:55characteristics of a company that,

00:08:57maybe too complex.

00:08:59Needs to be fixed.

00:09:01The recruitment system part.

00:09:04So what about The Best Onboarding?

00:09:06Kick-off.

00:09:08Your kick-off was like giving you a heads up.

00:09:09Eh,

00:09:12for the next 6 months,

00:09:13or for the next 3 months,

00:09:14for example, for example onboarding,

00:09:15You will do this, this, this, this, okay?

00:09:18This is your KPI,

00:09:20I expected you to be able to do this.

00:09:21That's it.

00:09:25My hope is that you can

00:09:27enter the team with conditions

00:09:29You can contribute this, this, this.

00:09:31Or for example like,

00:09:32oh, we already have a project,

00:09:33you enter this project section,

00:09:34You do A, B, C, D, U, F, D.

00:09:36That's a different stage from onboarding.

00:09:38Onboarding is really like,

00:09:40we adapt to

00:09:41just the company.

00:09:42With his team.

00:09:43This kick-off is really like,

00:09:44okay, it works like this.

00:09:46Just started work.

00:09:50Well, everything has to go through

00:09:521, 2, 3, 4, 5 stages.

00:09:55No work except.

00:09:57If we start using AI,

00:10:00usually go straight to,

00:10:02start work.

00:10:04Just like that,

00:10:06make it more casual.

00:10:09Why is your copywriting bad?

00:10:12remember how it was before.

00:10:15How?

00:10:16What do you remember?

00:10:18That's just how humans are.

00:10:20We're like,

00:10:21we like to underestimate

00:10:23our ability in communication,

00:10:25and like to underestimate

00:10:30communication level

00:10:31that we tell people.

00:10:33What do you mean?

00:10:34We have given,

00:10:35we'll let you know.

00:10:36But we won't tell you in detail.

00:10:38There is no context.

00:10:39Nothing.

00:10:40For people who

00:10:42maybe you haven't known us for long,

00:10:43maybe smarter,

00:10:44all kinds.

00:10:44Maybe he's fast.

00:10:46The problem is,

00:10:4899% of people are still at this level,

00:10:51still confused.

00:10:52Sometimes first,

00:10:53don't use expensive AI.

00:10:56I used to say,

00:10:56the problem is quite resolved.

00:10:58Maybe it's half done

00:10:59if we use it

00:11:00expensive model.

00:11:01That's the expensive one

00:11:02the average now is already a million.

00:11:041.7 a month.

00:11:08Just been able to exchange it like this.

00:11:11Or not.

00:11:15Get used to

00:11:18I don't know if there is a type of person like that

00:11:21maybe it's the level of communication

00:11:24unsharpened.

00:11:25Me too.

00:11:27So I'm really happy,

00:11:28nice to meet someone who

00:11:29if I say a little,

00:11:31he already understands.

00:11:32I don't need to say much.

00:11:34Minimal communication.

00:11:36What happened was

00:11:37fit in AI,

00:11:38It can't be like this.

00:11:40We can't be like that

00:11:40AI's silent treatment

00:11:41or passive-aggressive.

00:11:42Especially us Asians.

00:11:44Like passive-aggressive like,

00:11:45Is it really like that?

00:11:46do not understand.

00:11:48The AI is confused.

00:11:49It's like,

00:11:49this is a robot,

00:11:50not human.

00:11:51so he has to be us

00:11:55as if it were prepared first,

00:11:58polished like that.

00:12:00Only then can he work.

00:12:03So we,

00:12:05the ideal is

00:12:06treating AI

00:12:07at a glance, human,

00:12:09at a glance our employees.

00:12:11This applies to friends

00:12:12which still uses AI,

00:12:14for example use

00:12:17regular GPT code,

00:12:19or for example already using it

00:12:20agent,

00:12:21or like a pen call,

00:12:22all sorts of things like that.

00:12:23Because,

00:12:23there are so many people who

00:12:26ask me,

00:12:27oh can I use this,

00:12:27can use this.

00:12:28Can,

00:12:29everything is possible.

00:12:30The first problem,

00:12:31can you afford the cost?

00:12:33Tokens are expensive.

00:12:34Good tokens are expensive.

00:12:35There are so many people who,

00:12:36I think so,

00:12:37over claim like that.

00:12:38Parallel today

00:12:40made in April 2006,

00:12:43we don't know what the future holds,

00:12:44but in April 2006,

00:12:46so many people

00:12:47talking about open cloud.

00:12:48Open cloud it,

00:12:49be one of

00:12:50The most advanced AI,

00:12:52but cloud

00:12:54already closed open cloud,

00:12:56access.

00:12:57So if you want to use open cloud,

00:12:58must use the API.

00:12:59Many people now

00:13:00having open cloud is stupid.

00:13:02Because of what?

00:13:03Because of his brain,

00:13:05his open cloud debt brain,

00:13:06it must use opus 4.6.

00:13:08Now,

00:13:09if you don't use it,

00:13:10Bad.

00:13:11Critical.

00:13:12Really ugly.

00:13:14And,

00:13:15Now,

00:13:16most people

00:13:17who talks about open cloud,

00:13:18open cloud,

00:13:18that could be said,

00:13:21depend on,

00:13:22staff,

00:13:23super staff,

00:13:24who has it all.

00:13:26Once access is closed,

00:13:27the staff is dead.

00:13:28what can be done

00:13:29in a more intral way is,

00:13:31breakdown,

00:13:32pre-telling,

00:13:33its business process,

00:13:34which ones can be automated

00:13:36use AI,

00:13:37which ones can be automated

00:13:38use humans.

00:13:42like that.

00:13:43So,

00:13:44and which ones can be automated using code.

00:13:46That's different again.

00:13:47The code is like,

00:13:47he is more reliable.

00:13:49For example, yes,

00:13:50I just did it last night

00:13:51create a system,

00:13:52Where,

00:13:53I can share.

00:13:56this is still local.

00:13:58I have a book project.

00:14:02I am more than making books

00:14:04about a figure I admire.

00:14:10The Sovereign is,

00:14:12can i or not

00:14:14pull

00:14:16transcript

00:14:17from all YouTube

00:14:18which discusses this figure,

00:14:20Keep going

00:14:22analyzed

00:14:23when the character speaks,

00:14:25when other people talk,

00:14:27Keep going

00:14:28cross-checked

00:14:31Is the text suitable or not?

00:14:32can go to the subtitles.

00:14:33If there are no subtitles,

00:14:34we use

00:14:34local model named whisper

00:14:37for

00:14:38checking

00:14:39whether

00:14:41audio matches the text.

00:14:42So,

00:14:42he can translate

00:14:43from audio to text.

00:14:45Keep going

00:14:46made like

00:14:46world cloud like this.

00:14:48Which one is the most frequent?

00:14:49it's said

00:14:50with this character.

00:14:51There are only 7 videos,

00:14:52still a prototype,

00:14:52just made kayak

00:14:53about 2 hours

00:14:54last night.

00:14:56Now,

00:14:57If possible, use AI

00:14:58everyone can.

00:14:59Expensive.

00:15:00One video can

00:15:00Possible

00:15:01tens of thousands,

00:15:03tens of thousands

00:15:03depending on the duration of the video.

00:15:05So,

00:15:05what to do?

00:15:06Separated-able.

00:15:07Where's the human part?

00:15:09which part has the code,

00:15:11code in the sense

00:15:12like for example

00:15:12broken down like this,

00:15:13deep break,

00:15:14this is it

00:15:15cracked

00:15:16like this world cloud, right?

00:15:17actually the functions

00:15:18the count,

00:15:19keep counting.

00:15:19no need to use AI.

00:15:22No need to use AI

00:15:23I mean like AI

00:15:23who read all

00:15:24that's not necessary.

00:15:25Expensive.

00:15:26So,

00:15:26we use functions

00:15:27just a normal count,

00:15:28counting function,

00:15:29like a formula in Excel,

00:15:30sum if,

00:15:31all sorts.

00:15:32Keep going,

00:15:33if it's the AI part,

00:15:35after we level it

00:15:35one by one,

00:15:36the AI part is

00:15:37the most important thing is

00:15:39determine

00:15:39who said what.

00:15:42Who said that?

00:15:43when did Mr. Gita speak,

00:15:45when the host speaks,

00:15:47when for example

00:15:47other sources said.

00:15:48That's the most important thing,

00:15:49while tidying up the text.

00:15:51Already,

00:15:52the rest is not necessary,

00:15:53and it can use AI

00:15:54the cheaper one,

00:15:55because the rest of us

00:15:56can use code.

00:15:58Now,

00:15:58our ability to differentiate

00:15:59when humans,

00:16:01when code,

00:16:01when AI,

00:16:02this is increasingly needed

00:16:03in the era

00:16:04where are we

00:16:05feel now

00:16:06AI has become an employee.

00:16:08like that,

00:16:09So

00:16:11on-work AI to the team

00:16:12That is not

00:16:13like we have AI

00:16:14the super one

00:16:15do everything.

00:16:16Of course you can,

00:16:17if you have a budget

00:16:18Possible,

00:16:19This,

00:16:19I'll just give you an estimate, okay?

00:16:21the budget is possible

00:16:21can be around

00:16:22thousands of dollars

00:16:24until

00:16:24tens of thousands of dollars

00:16:26per month

00:16:27if we use API

00:16:28the good one.

00:16:30Why?

00:16:30Because it's expensive.

00:16:32Because every time

00:16:32he read

00:16:33use tokens,

00:16:34every time he makes a decision

00:16:36use tokens,

00:16:36every time he gives it to us

00:16:38use tokens.

00:16:38So it's like there's input,

00:16:40there is a process,

00:16:40there is output.

00:16:41Everything uses tokens.

00:16:42It's expensive.

00:16:44So how

00:16:44the set is

00:16:45How to do?

00:16:46For example

00:16:46input does not use tokens

00:16:48If I.

00:16:49The input is using code,

00:16:50use humans.

00:16:52Of course I do,

00:16:52this is what he wants his life to be like,

00:16:53this, this, this.

00:16:53I did my own research

00:16:54or I ask AI

00:16:55search but

00:16:56with cheaper costs,

00:16:58like that.

00:16:58Separate the process.

00:17:00If not,

00:17:01yes unless friends

00:17:02when does the owner have it?

00:17:03very large resources,

00:17:05will

00:17:05have limitations in the boarding house

00:17:07or if for example

00:17:08use free AI,

00:17:09BT itself,

00:17:11The AI is stupid,

00:17:12like that.

00:17:14Stupid AI,

00:17:15like that,

00:17:15usually can do it,

00:17:16actually not stupid,

00:17:17but he can't do it

00:17:18something complex.

00:17:19He can do it

00:17:20simple things.

00:17:22Now,

00:17:22We can also differentiate this.

00:17:24We

00:17:24recruit the right AI

00:17:26or not

00:17:26in the first part.

00:17:28If we recruit AI

00:17:29appropriate,

00:17:30we can get that

00:17:31the quality that

00:17:32according to what we want.

00:17:34There is a price,

00:17:34there are items.

00:17:35A lot of

00:17:36who tried open clause

00:17:37all kinds

00:17:37still using the free one.

00:17:38Hope that

00:17:39there is free technology

00:17:41who can solve everything.

00:17:43Sadly,

00:17:44not like that.

00:17:45The faster we are

00:17:46accept reality

00:17:47that

00:17:48is that AI?

00:17:50paid,

00:17:51and we have to

00:17:52search for ROI

00:17:53as soon as possible,

00:17:54getting faster too

00:17:55We

00:17:59Can

00:17:59leverage AI.

00:18:00Many people in Indonesia,

00:18:02especially people

00:18:03GPT Learning Member

00:18:04not like that.

00:18:04People who want to join

00:18:05Learn GPT

00:18:06those who don't join,

00:18:07it always has limitations

00:18:09to,

00:18:09Okay,

00:18:09This AI is expensive,

00:18:10I don't have any money.

00:18:12Or like,

00:18:12oh can i use it or not

00:18:13Free AI.

00:18:13That's the wrong mindset.

00:18:15Because AI will stay,

00:18:17AI is here to stay.

00:18:18His thoughts now are

00:18:19how can we do it

00:18:21get the ROI.

00:18:23This AI can be used

00:18:23What for.

00:18:25And the choice

00:18:26to lend AI

00:18:27the cheaper one,

00:18:28more

00:18:31more affordable,

00:18:32it makes sense.

00:18:33If we have

00:18:33retelin

00:18:36workflow.

00:18:38But if for

00:18:39daily,

00:18:40ideally we

00:18:41always use the most expensive.

00:18:42If we use API,

00:18:44of course we need to use it

00:18:45the usual bag,

00:18:46we use the cheap ones,

00:18:47the good one,

00:18:48we use the expensive ones.

00:18:51Only after that

00:18:51we onboard the AI to the team,

00:18:53we teach,

00:18:53Our workload is like this, you know?

00:18:54onboard to the team

00:18:55what does that mean?

00:18:56we explain,

00:18:57What is our center?

00:18:59What are we going to teach?

00:19:00What is our project?

00:19:01There is something called context.

00:19:03Hence why

00:19:04it's called context engineering.

00:19:07Okay?

00:19:08That context

00:19:08who are we?

00:19:10We are,

00:19:10we engine,

00:19:11we are personal,

00:19:11who are we?

00:19:12What do we like?

00:19:14What kind of AI do we need?

00:19:17What are we going to do?

00:19:18Which way are we going?

00:19:19Many people can't

00:19:20explain who we are?

00:19:22For example, who is that?

00:19:23For example, kayaking

00:19:24I want to make a YouTube video.

00:19:26if you just type like

00:19:27I am

00:19:30a YouTuber

00:19:31blah, blah, blah,

00:19:31can't guys.

00:19:33I'll explain

00:19:33just a little bit.

00:19:35How do I do it?

00:19:38use YouTube?

00:19:41This

00:19:43this is the old prom,

00:19:44so I can share.

00:19:45I already have a prom

00:19:46newer ones.

00:20:02There must be a question, why use English?

00:20:07AI apparently uses English, first.

00:20:09And secondly, the tokens can be more economical if you use English.

00:20:11And thirdly, I think, that's it.

00:20:17We are living in an age where we have to accept the facts.

00:20:20English is indeed a universal language.

00:20:23Learn like that.

00:20:25So, what's the tone, content, principle, all sorts of things.

00:20:30So, I won't get to the bottom of this, because it's long.

00:20:33It's like 1000-1500 words.

00:20:36But, if I just type,

00:20:38please make a good YouTube script,

00:20:41yeah it's nothing.

00:20:43He has to complete this.

00:20:45Why?

00:20:45Because to make a YouTube script,

00:20:48or any content, yes,

00:20:49He should know who we are.

00:20:51We are,

00:20:55What's the tone, what's our background?

00:20:57What is our uniqueness compared to other regular content?

00:21:00So he can adjust.

00:21:01What is permissible and what is not permissible.

00:21:03Things like this are like,

00:21:05for example, what type of content do we want?

00:21:07do you want to be like that,

00:21:09for example, there is palace content that works,

00:21:12giving it like some kind of controversy all the time.

00:21:15There are those who prefer to provide evidence first,

00:21:18how analytical, all sorts,

00:21:20there is science driven, not like that.

00:21:22Well, that's how we choose,

00:21:23which one do we want?

00:21:25We have to let you know,

00:21:26we have to give a brief.

00:21:28Imagine like,

00:21:29back to this,

00:21:30imagine like a human.

00:21:34We have a passion,

00:21:35freelance human, yes.

00:21:36So he didn't miss out on the jazz job,

00:21:38interview,

00:21:39onboarding,

00:21:40kick off straight to work.

00:21:42Please make a YouTube script.

00:21:45Lep.

00:21:47This is really good.

00:21:49This is too professional.

00:21:51This is too much,

00:21:52too much like this.

00:21:53Why?

00:21:53Since we are just briefing,

00:21:55please-then make a YouTube script.

00:21:56Just a human,

00:21:57if we do that,

00:21:58Confused,

00:21:59upload on AI.

00:22:02Imagine that.

00:22:05Just kicked off with AI,

00:22:06just working with AI.

00:22:08There are many ways to work with AI.

00:22:11So,

00:22:12This framework hasn't touched on the AI agent yet,

00:22:14but the way it works is very-very-very similar.

00:22:18What,

00:22:19how do we make it interact with AI?

00:22:22There are two ways.

00:22:23Chatbot and AI agent.

00:22:25Later I will showcase my use of AI agent.

00:22:29Usually I use cloud code.

00:22:31So,

00:22:32there are lots of AI agent software,

00:22:33like let's say for example,

00:22:36Rapport,

00:22:37or for example what?

00:22:38There are various kinds.

00:22:39Many Hindus also make it.

00:22:40But my analogy is always like this.

00:22:44The AI agents are made by people,

00:22:47it's like a reseller.

00:22:49Token reseller.

00:22:51What do you mean?

00:22:53His brain,

00:22:53What is the AI agent's brain?

00:22:55There are only three good ones.

00:22:56Cloud,

00:22:57Bimini,

00:22:58CGPT.

00:22:59So,

00:22:59if we make it for example,

00:23:00use AI agents other than these three,

00:23:02we use AI agents from the reseller.

00:23:06These three people.

00:23:07The question is,

00:23:09Does the reseller have additional added value?

00:23:12what don't these three have?

00:23:14If not,

00:23:15It's better to buy it here.

00:23:17And this answers the question,

00:23:19can you use Kayak?

00:23:21I don't mention brands,

00:23:22but there are lots of local ones,

00:23:26local product that makes AI that can access everything.

00:23:29The analogy is also the same.

00:23:32For example, if

00:23:33rough and distributor,

00:23:35the main thing,

00:23:38the main principle,

00:23:39just like the brand itself,

00:23:41sell for 20 dollars,

00:23:42How can someone sell it at a cheap price?

00:23:46then can let go of everything.

00:23:47There must be something sacrificed.

00:23:51That's the key right there.

00:23:52If you want to know,

00:23:53can you not bring GPT,

00:23:54so that we make a lot of fun of people like that.

00:23:57Okay.

00:23:58Then there are chatbots.

00:23:59Chatbots are simple.

00:24:00For example, we open a chatbot.

00:24:03I'm using the cloud.

00:24:05O.

00:24:06I use the somat one,

00:24:07so you don't have to apologize.

00:24:08O.

00:24:09Would you like me to ask you a question?

00:24:18Just random.

00:24:24About trivia.

00:24:28Try chatting with me.

00:24:31How?

00:24:34This we call using

00:24:39AI like Google.

00:24:41It's just like a question and answer session.

00:24:49It really is like we are friends.

00:24:52Like we're just playing around.

00:25:00What?

00:25:01Octopus blood.

00:25:03What is it?

00:25:07Black?

00:25:09Yes, right.

00:25:18Blue.

00:25:22Emotional.

00:25:23Potenya uses nebaga.

00:25:28Oh.

00:25:29Okay.

00:25:30Now.

00:25:30This is an interesting trick, isn't it?

00:25:33We can use AI.

00:25:34Now.

00:25:35We use slides.

00:25:35So we

00:25:38We are the AI

00:25:39Here's the AI side.

00:25:40He received the prompt

00:25:41Then he responded.

00:25:42So he

00:25:42His type is very passive.

00:25:44He just started working

00:25:46If we

00:25:48Order

00:25:49Then he answered.

00:25:50Luckily the answer was quick.

00:25:52AI agent

00:25:53That's it he can do

00:25:56Got a prompt.

00:25:58He

00:25:59Planning the prompt.

00:26:00He has a step-by-step.

00:26:01He has external tools.

00:26:02He can work alone

00:26:04Without

00:26:04Our call.

00:26:06And he's new

00:26:07Prompt response.

00:26:09And he can

00:26:10Excess

00:26:10Agents

00:26:11Agents

00:26:11Is

00:26:11He can

00:26:12Deploy

00:26:13Another AI agent.

00:26:14I don't use it here

00:26:15Fancy tools, huh?

00:26:17Again me

00:26:18If in

00:26:19For GPT it is

00:26:19We are quite fundamentalist.

00:26:21So

00:26:21We use it

00:26:23AI Tools

00:26:23Which is true

00:26:24It's really been proven.

00:26:26There are none anymore

00:26:26Bugs of all kinds

00:26:27Secure.

00:26:28Our open cloud

00:26:28Not yet entered.

00:26:29So far.

00:26:30And we always prefer

00:26:33The main brand.

00:26:34We never

00:26:35Recommendations

00:26:35Wearing a tie

00:26:36The resellers.

00:26:38Always the main brand.

00:26:39Cloud

00:26:39GPT

00:26:41Gemini.

00:26:42Already.

00:26:44Now

00:26:44Here's an example

00:26:46AI agent.

00:26:47I wear it

00:26:48Cloud.

00:26:51Well this is the name

00:26:52Cloud Code.

00:26:53Cloud Code is

00:26:54Cloud

00:26:54The living

00:26:55In

00:26:56Our computer.

00:26:57My computer

00:26:58More correctly.

00:26:59Friends can check

00:27:00Method

00:27:01How do you use it?

00:27:06Now

00:27:07O.

00:27:11Let's test this, okay?

00:27:13So if we use it

00:27:13Agent

00:27:14That's it he can do

00:27:15Can do assignments

00:27:16He can be like

00:27:17It's just like usual

00:27:18For example, kayaking

00:27:18O

00:27:19Can you

00:27:20Give me

00:27:21Review

00:27:23He can

00:27:24As usual

00:27:30I

00:27:33Know

00:27:35Oh

00:27:39Wait

00:27:41I know

00:27:42The

00:27:43Fifth

00:27:46Vicar

00:27:50Or

00:27:51I

00:27:52Think

00:27:53Is

00:27:53Take note

00:28:00Oh

00:28:01One

00:28:02News

00:28:02Okay

00:28:03Now

00:28:04This is what we are like

00:28:05Trivia

00:28:06It's normal, yeah?

00:28:06We use it every day

00:28:07We can too

00:28:08Clear

00:28:09We can say like

00:28:10O

00:28:11Help me

00:28:14Deploy

00:28:15Three agents

00:28:17Research

00:28:18About

00:28:19The

00:28:21Impact

00:28:22Of

00:28:23Hormuz

00:28:26To

00:28:28Indonesian

00:28:28Economy

00:28:32Five years

00:28:34From now

00:28:35Or

00:28:36Two years, huh?

00:28:37Five years

00:28:37Page

00:28:37And

00:28:39What should

00:28:41I

00:28:43US

00:28:44Middle

00:28:46Income

00:28:47Individual

00:28:48Prepare

00:28:54Okay

00:28:54So this is it

00:28:56AI agent create

00:28:57Research yeah

00:28:58This is for

00:28:58Just a demonstration

00:29:00Now

00:29:00The way he works

00:29:02We can do it here

00:29:03Like he's there

00:29:03Thinking

00:29:03Deployed now

00:29:05So

00:29:06It seems he has

00:29:07Own ability

00:29:08For

00:29:08Planning

00:29:09How it works

00:29:10How

00:29:10That's the difference

00:29:11AI agent same

00:29:12The usual

00:29:13So

00:29:14We see here he is

00:29:15There is one agent

00:29:16Hormuz impact

00:29:17On Indonesia

00:29:18Macro

00:29:18So he can

00:29:20Let's just see here

00:29:24Two agents

00:29:25So there is

00:29:26Hormuz

00:29:27Geotechnical

00:29:27Scenarios

00:29:30And here we are

00:29:31Just leave it

00:29:32Sometimes this can be

00:29:32Two minutes

00:29:33Three minutes

00:29:34Sometimes it can

00:29:35Ten minutes

00:29:35Sometimes it can

00:29:3615 minutes

00:29:37This is hopefully

00:29:38We just stay

00:29:39He can walk by himself

00:29:43Now

00:29:43His abilities

00:29:44That's enough

00:29:46Mind-blowing

00:29:46Because

00:29:47EHA agent can do it

00:29:51If it remains

00:29:52Do some research, okay?

00:29:52And coding

00:29:53And the bags that are needed

00:29:55Time

00:29:55Need a kayak

00:29:56Multi-step

00:29:57He can already

00:29:58Alone

00:29:59So

00:30:00To give you an idea

00:30:01Before

00:30:02Not before

00:30:03It's like last year, right?

00:30:04I made it

00:30:05Workshop right?

00:30:06Can be on the moon

00:30:07The GPT learner

00:30:08This is it

00:30:10Workshop

00:30:11Prompt Engineering

00:30:11It's been a while

00:30:12We make it from scratch

00:30:13But

00:30:16Prompt Engineering Workshop

00:30:17This is it

00:30:18Usually

00:30:21I always recommend

00:30:22Use a long prompt

00:30:23But

00:30:24Since there was

00:30:26EHA agent

00:30:27The prompt could be shorter

00:30:28But indeed

00:30:29We have to define

00:30:30Very clear

00:30:31The steps

00:30:31Every

00:30:32Because of what

00:30:33Because of EHA

00:30:34Getting smarter

00:30:35But for

00:30:36Got it

00:30:36This EHA

00:30:38I use cloud max

00:30:39So cloud max

00:30:40That's the 100 dollar one

00:30:40A month

00:30:41If friends use the one

00:30:4220 dollars a month

00:30:43Can also

00:30:43It will just happen often

00:30:44Hit the limit

00:30:45Like my team

00:30:46We use the 20 dollar one

00:30:47A month

00:30:48Maybe sometimes

00:30:49Once a day

00:30:50There's a limit

00:30:54Here

00:30:55We are still waiting

00:30:56Let's just wait

00:31:01While

00:31:03Waiting

00:31:04Again for friends who

00:31:07Just watched

00:31:08Just found my channel

00:31:09Possible

00:31:09New

00:31:10Watching GPT learning

00:31:11What is that

00:31:12This

00:31:13I share it for free

00:31:14On YouTube

00:31:14We don't exist

00:31:15Cover-ups

00:31:16All of these

00:31:16The workshop is all that can be done

00:31:18I share

00:31:18Paid

00:31:19Our class is quite expensive

00:31:20But

00:31:21I only ask for one

00:31:23If friends

00:31:24I found this helpful

00:31:25We are kind of friends

00:31:28Friends must be gentle

00:31:29If for example this is useful

00:31:30Friends must subscribe

00:31:31My channel

00:31:31That's all

00:31:33Already

00:31:35Winning economic impact

00:31:36This is so he has

00:31:37Three agents

00:31:38If we ask for three

00:31:39Three

00:31:39If he asks for ten

00:31:40Ten

00:31:40But sometimes it can also

00:31:42Like he automatically thinks

00:31:43Approximately how many agents are needed?

00:31:45And this is like

00:31:45Seven tools

00:31:46Use

00:31:466 tools

00:31:47This is what he's like sometimes

00:31:48Browse first

00:31:48What did he do first?

00:31:49We don't know

00:31:58Current state

00:31:59Indonesia already

00:32:01Rupiah already

00:32:0212,000

00:32:04CPI this much

00:32:06BI rate is this much

00:32:07The probability is

00:32:11Malk

00:32:12It can

00:32:137500

00:32:14Minus 0.3

00:32:16Moderate

00:32:170.8

00:32:19Same 1.2

00:32:20Civil can

00:32:21Up to 20,000

00:32:22Our Rupiah

00:32:23CPI

00:32:24Our GDP is minus 2%

00:32:26Keep going like this

00:32:27Fuel will be limited

00:32:29The state budget will be in recession

00:32:33Geopolitical

00:32:34Almost never close

00:32:35In 45 years

00:32:40Okay

00:32:40So

00:32:41What should we do?

00:32:43Take the nature

00:32:44We have to make it longer

00:32:466-9 months

00:32:47Because

00:32:48For example, if

00:32:49Oil rises

00:32:50So

00:32:52More layoffs

00:32:53And prices are all going up

00:32:55Our liquidity must break

00:32:57Partly to USD

00:32:57Not only that

00:32:58Not just rupiah

00:32:59Because

00:32:59Certain

00:33:01Rupiah will

00:33:02Increasingly rising

00:33:03Digital bank

00:33:05Suga macem

00:33:06Gold

00:33:07Can be used

00:33:08Gold fight

00:33:09Keep going like this

00:33:10Pay

00:33:10Pay all floating

00:33:11The rate

00:33:12Or you can

00:33:12Ask for

00:33:13Negotiable

00:33:14There isn't any

00:33:16There isn't any

00:33:17The debt that

00:33:18Denominated

00:33:19Use dollars

00:33:20Continue LPG

00:33:22Transport

00:33:23Bookstock

00:33:24File

00:33:28Keep going like this

00:33:29Coal

00:33:31Remember that

00:33:31Will go up

00:33:32In the future

00:33:34Then have to have

00:33:35BPJS

00:33:37Don't

00:33:37Sell first

00:33:42Keep on existing

00:33:43Some caveats

00:33:44The first caviat is

00:33:45Agent 2

00:33:46Geopolitical, that is.

00:33:47Don't use it

00:33:48Web Access

00:33:48And he

00:33:49Using data

00:33:502025

00:33:51So

00:33:52There must be

00:33:54The deviation

00:33:55Around 10-15%

00:33:56No

00:33:56Not fresh

00:33:58If it's agent 1

00:33:59Use a browser

00:34:00And he can

00:34:02Seen

00:34:02What's the list?

00:34:03So

00:34:04We have

00:34:05Like this kind of thing

00:34:06There are internals who have

00:34:08Many other interns

00:34:09So like

00:34:09Hey, look for it

00:34:10Suddenly said

00:34:11Kayak

00:34:11Hey come on

00:34:12Search-search-search-search

00:34:13There will be another one later

00:34:14The one who collects

00:34:14The difference is

00:34:15Usually

00:34:16This takes time

00:34:17Maybe all day

00:34:18This takes time

00:34:192 minutes 42 seconds

00:34:20This is the agent

00:34:21Another agent we can use is

00:34:23Clear

00:34:25Hi

00:34:26Helming create

00:34:27Simple

00:34:29Blending page

00:34:30For

00:34:31Let's say

00:34:32For example, we are like

00:34:33What is it

00:34:34Promoting

00:34:38Literacy

00:34:39Financial

00:34:41Literacy

00:34:42Or

00:34:43Pension

00:34:48Age

00:34:49People

00:34:50In Indonesia

00:34:53100

00:34:55Leverage

00:34:55100

00:35:26Many

00:35:27If

00:35:28Use

00:35:29Agent

00:35:30Many

00:35:31I'm waiting

00:35:31The agent

00:35:33What are you doing

00:35:42Pension

00:35:43Cipadas

00:35:53Pension

00:35:53Cipadas

00:35:53This is in

00:35:54How many seconds?

00:35:5549 seconds

00:35:57Notice yes

00:35:59A lot of

00:36:00Now

00:36:00Not breathing

00:36:00Like this

00:36:01At first

00:36:01His phone

00:36:02Like this

00:36:03This

00:36:04Like this

00:36:04Paid

00:36:05Like this

00:36:05And this

00:36:05It's very good

00:36:08This

00:36:09Is

00:36:10Type

00:36:11Learning page

00:36:12What was made

00:36:12Same AI

00:36:12This is direct

00:36:13So

00:36:13Direct

00:36:14Can

00:36:15Copied

00:36:15To

00:36:16Can

00:36:17To

00:36:18Wherever

00:36:19If

00:36:20For example

00:36:20Server

00:36:21Or

00:36:22For example

00:36:23If

00:36:24In

00:36:24Workshop

00:36:24I

00:36:25So

00:36:25To

00:36:25One

00:36:26Site

00:36:27We

00:36:27Can

00:36:28Upload

00:36:28Free

00:36:31Direct

00:36:31So

00:36:33So

00:36:34This is it

00:36:36In the future

00:36:37AI will be

00:36:38Like this

00:36:38He will be right away

00:36:39Control

00:36:39Everything that exists

00:36:40On our computer

00:36:41Sometimes we may

00:36:41No need for a computer

00:36:42Good again

00:36:43As long as he can

00:36:44Imprisoning

00:36:45AI

00:36:45So

00:36:46He can

00:36:47Accept

00:36:47Prom

00:36:47Keep going

00:36:47He can

00:36:48Plan

00:36:48Work

00:36:49Step-by-step

00:36:49He did it himself

00:36:50He needs to

00:36:51External tools

00:36:52He is browsing

00:36:53What is he doing?

00:36:53If necessary

00:36:54He just replied

00:36:55Nothing is direct

00:36:56Bales

00:36:57Fast

00:36:57But

00:36:57Asbun

00:37:01Now

00:37:01That's it

00:37:02Now

00:37:03The role is

00:37:04We must

00:37:05Check out

00:37:05What kind of AI is it?

00:37:08Okay

00:37:10Take a breath first

00:37:13Tired too

00:37:14Talk

00:37:1437 minutes

00:37:17Now

00:37:17This

00:37:19Example

00:37:19Simple LLM

00:37:20So

00:37:21LLM

00:37:21It means

00:37:22Last language model

00:37:27Machine

00:37:27Behind

00:37:28AI that exists today

00:37:29Or

00:37:29For example, it is said

00:37:30Training model

00:37:31What exists now

00:37:31Last language model

00:37:33So like

00:37:33For example, if

00:37:34People come in

00:37:34Joko

00:37:35Oh

00:37:35Possible

00:37:36This is the president's finger

00:37:37Wow

00:37:38Breakthrough

00:37:39Bianto

00:37:39123

00:37:40Point

00:37:415

00:37:41In the middle

00:37:424

00:37:42Sukarno

00:37:43But

00:37:44If we enter

00:37:45Jack

00:37:45I'm confused

00:37:47This is Jack

00:37:47Mom

00:37:48Jack Sparrow

00:37:50Jack Smith

00:37:51Jack

00:37:52What is it?

00:37:54Why

00:37:55Because

00:37:58This

00:37:59Including

00:38:00The word that

00:38:01Multiple interpretations

00:38:02Term

00:38:03He can

00:38:04Whatever

00:38:05And

00:38:06There isn't any

00:38:06Special pattern

00:38:07Different

00:38:08Same for example

00:38:08Likely possible

00:38:09If people

00:38:10Typing

00:38:10Joko

00:38:13Big

00:38:14Presentation

00:38:14Person

00:38:14Indonesia

00:38:15Especially

00:38:15That will be

00:38:16Typing it

00:38:16Wow

00:38:16Or

00:38:17For example, if

00:38:17Pembu

00:38:18It's certain

00:38:18Sudian

00:38:18But

00:38:19If Jack

00:38:20It's like

00:38:21Lots

00:38:21This can

00:38:22Jack

00:38:23Whatever

00:38:24Now

00:38:25Pro-engineering

00:38:27It is

00:38:27How to make us

00:38:28Can

00:38:28Directing

00:38:29Jack

00:38:31This can

00:38:31The output

00:38:32What is it

00:38:33Can

00:38:34Jack

00:38:34Whatever

00:38:35So

00:38:35Because of us

00:38:36Direction

00:38:36So

00:38:37This AI

00:38:38I have it

00:38:39The model that

00:38:39Trained

00:38:40Like earlier

00:38:41We will

00:38:41For example

00:38:41In

00:38:43Here

00:38:45I have

00:38:46Push again

00:38:51Earlier below

00:38:52This is what

00:38:52Notes

00:38:52Which

00:38:52It is said

00:38:53If

00:38:55Geopolitical

00:38:56Agent

00:38:56It is said

00:38:57If

00:38:57He

00:38:57The data

00:38:57Final

00:38:58Relatively

00:38:58In

00:38:58May

00:38:592025

00:39:01So

00:39:03AI

00:39:03That

00:39:04There is

00:39:04Data

00:39:04The input

00:39:05Method

00:39:06We

00:39:07Interesting

00:39:08Data

00:39:08The input

00:39:08Is

00:39:09We

00:39:09Use

00:39:10ROM

00:39:11Keep going

00:39:12Can

00:39:12Use

00:39:12CGPT

00:39:13Use

00:39:13Whatever

00:39:16Model

00:39:16Most

00:39:17Good

00:39:17This

00:39:17Rather

00:39:17Left behind

00:39:18Model

00:39:19Most

00:39:19Good

00:39:20Now

00:39:20If

00:39:21CGPT

00:39:22That

00:39:22Is

00:39:23CGPT

00:39:235.4

00:39:25Pidu

00:39:26In addition

00:39:26Okay

00:39:27Is

00:39:27He

00:39:27There is

00:39:27In

00:39:27Research

00:39:28He

00:39:28There is

00:39:28Agent

00:39:28He

00:39:29Sora

00:39:30But

00:39:30Final

00:39:30As far as I know

00:39:31I

00:39:31Sora

00:39:31Again

00:39:31In

00:39:32Shardown

00:39:32So

00:39:33Possible

00:39:33Still

00:39:34There is

00:39:34Limited

00:39:35Sora

00:39:36Social Media

00:39:36The sound

00:39:38Here

00:39:38Still

00:39:38There is

00:39:39Cloud

00:39:40Cloud

00:39:41Opus

00:39:41That

00:39:42The best

00:39:43Now

00:39:44Even

00:39:45The best

00:39:45For

00:39:45Everything

00:39:46For

00:39:46Think

00:39:47For

00:39:47Research

00:39:48For

00:39:48Agent

00:39:49All

00:39:49Various

00:39:49That

00:39:50Most

00:39:51The best

00:39:51Cloud

00:39:52Opus

00:39:534.6

00:39:54If

00:39:55Gemini

00:39:55That

00:39:56Now

00:39:56It can be said that

00:39:57The most

00:39:57Okay

00:39:57For

00:39:58The money

00:39:59Value

00:40:00For

00:40:00Money

00:40:00If

00:40:01Friends

00:40:01Buy a package

00:40:02Gemini

00:40:02AI

00:40:03Pro

00:40:03Which

00:40:03If

00:40:04No

00:40:04I

00:40:04Can

00:40:055

00:40:06Tera

00:40:06Google

00:40:07Drive

00:40:07I

00:40:08Buy

00:40:09Gemini

00:40:09AI

00:40:09Pro

00:40:10Actually

00:40:10Because

00:40:10Google

00:40:11Drive

00:40:11Only

00:40:12Keep going

00:40:12We

00:40:13Can

00:40:13Integration

00:40:14Google

00:40:14Apps

00:40:14Can

00:40:15Can

00:40:15Veo

00:40:15Can

00:40:16LM

00:40:16Nice

00:40:17Very

00:40:17Now

00:40:18If

00:40:18No

00:40:18I

00:40:18There is

00:40:18Gemini

00:40:19Three

00:40:20Which

00:40:21Interesting

00:40:21In AI

00:40:22That

00:40:22Every

00:40:22Month

00:40:23The capital

00:40:24Update

00:40:24Keep going

00:40:26It means

00:40:26How

00:40:26So

00:40:27For example

00:40:27This

00:40:28Data

00:40:28If

00:40:28No

00:40:28Sala

00:40:28Possible

00:40:29How many

00:40:29Month

00:40:29Which

00:40:30So

00:40:30But

00:40:30Already

00:40:31Different

00:40:31Again

00:40:31Month

00:40:32Front

00:40:32Different

00:40:33Again

00:40:33I

00:40:33Once

00:40:34Make

00:40:34Workshop

00:40:35Sunday

00:40:35That

00:40:35There is

00:40:36Model

00:40:36Water

00:40:36New

00:40:36So

00:40:36After

00:40:37I

00:40:37In

00:40:37Update

00:40:38Which

00:40:39Need

00:40:39We

00:40:39Know

00:40:40What

00:40:40According to

00:40:40I

00:40:40Only

00:40:40One

00:40:41Only

00:40:42There is

00:40:42Three

00:40:42Again

00:40:42Now

00:40:43Which

00:40:43Most

00:40:43Okay

00:40:43We

00:40:44No

00:40:44You know

00:40:44In the future

00:40:45How

00:40:45But

00:40:45Minimum

00:40:46We

00:40:46You know

00:40:46What

00:40:46Just

00:40:48CSGPT

00:40:48Cloud

00:40:49Gemini

00:40:49CSGPT

00:40:50Have

00:40:50Open AI

00:40:51Cloud

00:40:51Have

00:40:51Antrophic

00:40:52Gemini

00:40:52Have

00:40:53Google

00:40:55We

00:40:55Only

00:40:56Need

00:40:56You know

00:40:56AI

00:40:57Which

00:40:57Need

00:40:57We

00:40:58Use

00:40:58Just

00:40:58Lots

00:40:59Which

00:40:59Talk

00:41:00For example

00:41:00Oh

00:41:01Dipsick

00:41:02Good

00:41:02Here

00:41:05GLM

00:41:05Good

00:41:07Kimi

00:41:07Good

00:41:09But

00:41:09Usually

00:41:10Person

00:41:10Talk

00:41:10That

00:41:10First

00:41:11Use

00:41:12Which

00:41:12Use

00:41:12Normal

00:41:13No

00:41:13Use

00:41:13Which

00:41:13Pay

00:41:15Or

00:41:15Its purpose

00:41:16So

00:41:16Disspecific

00:41:17So

00:41:18If

00:41:18For

00:41:18Person

00:41:18And

00:41:19Usually

00:41:20For

00:41:20Coding

00:41:22Or

00:41:23For example

00:41:23Make

00:41:24Application

00:41:24Which

00:41:24There is

00:41:24FIRE

00:41:25Kayak

00:41:25I

00:41:25Make

00:41:26One

00:41:26App

00:41:26I

00:41:27No

00:41:27Can

00:41:27Discus

00:41:27But

00:41:28That

00:41:29Will

00:41:29There is

00:41:29AI

00:41:30And

00:41:32Ideal

00:41:32I

00:41:33Search

00:41:33AI

00:41:33Which

00:41:33Reasonable

00:41:34Cheap

00:41:34AI

00:41:34China

00:41:35Cheap

00:41:35But

00:41:37For

00:41:37We

00:41:37A day

00:41:40Make

00:41:40We

00:41:41Need

00:41:41Use

00:41:41What

00:41:41Already

00:41:42Use

00:41:42Which

00:41:42Tijanya

00:41:42This

00:41:43Already

00:41:43Most

00:41:43Right

00:41:43If

00:41:44I

00:41:44Can

00:41:44Ranking

00:41:45I

00:41:46Will

00:41:46Possible

00:41:46For

00:41:46Person

00:41:47Which

00:41:47Body

00:41:47General

00:41:47In

00:41:48Mini

00:41:49Cloud

00:41:49CGPT

00:41:50But

00:41:50If

00:41:50Friends

00:41:51Need

00:41:52Which

00:41:53Power

00:41:54Which

00:41:54More

00:41:54Fast

00:41:54I

00:41:55Will

00:41:55Prefer

00:41:56Cloud

00:41:56But

00:41:56100

00:41:57Dollar

00:41:58That

00:41:58Already

00:41:58Smart

00:41:59Can

00:42:00Doing it

00:42:00Everything

00:42:01Can

00:42:01Coding

00:42:01Can

00:42:02What

00:42:02Can

00:42:03All

00:42:06Now

00:42:09This

00:42:09Back again

00:42:10To

00:42:10Earlier

00:42:10Yes

00:42:11Method

00:42:12Merikul

00:42:12AI

00:42:15We

00:42:15Must

00:42:15Study

00:42:16Write

00:42:16Job

00:42:16Description

00:42:17Good

00:42:17For

00:42:18Can

00:42:18Look for

00:42:19AI

00:42:19Which

00:42:19Appropriate

00:42:20Because

00:42:21Lots

00:42:21Person

00:42:21Lots

00:42:22Very

00:42:23Person

00:42:23Come

00:42:23To

00:42:23I

00:42:23With

00:42:24Listen

00:42:24Kayak

00:42:25Bro

00:42:26Sir

00:42:28How come

00:42:28AI

00:42:29This

00:42:30Good

00:42:31No

00:42:35Gemini

00:42:36Good

00:42:36No

00:42:36Cloud

00:42:37Good

00:42:37No

00:42:37This

00:42:38Good

00:42:38No

00:42:38That

00:42:39Good

00:42:39No

00:42:39I

00:42:40Don't

00:42:40Know

00:42:41You

00:42:41Want to

00:42:41What are you doing

00:42:43Possible

00:42:43If

00:42:44Friends

00:42:44Study

00:42:44GPT

00:42:44Already

00:42:45Know

00:42:45Usually

00:42:46If

00:42:46Person

00:42:46Ask

00:42:47Kayak

00:42:47That's it

00:42:47I

00:42:48Will

00:42:50Ask

00:42:51Before

00:42:51With

00:42:52Enough

00:42:52Lots

00:42:52Because

00:42:53That

00:42:53Promissory note

00:42:54Very

00:42:54Basic

00:42:55I

00:42:55Say

00:42:56I

00:42:57That

00:42:57Already

00:42:57Clear

00:42:58No

00:42:58Once

00:42:58Watch

00:42:59Module

00:43:00Buy

00:43:00Only

00:43:00Usually

00:43:00But

00:43:01I

00:43:01Can

00:43:01Maren

00:43:06Now

00:43:06No

00:43:07Can

00:43:07Tatooin

00:43:08Where

00:43:08Good

00:43:08Depends

00:43:09Want to

00:43:09Use

00:43:09What

00:43:10For

00:43:10What

00:43:10Budget

00:43:11How many

00:43:11And

00:43:12Method

00:43:13Most

00:43:14Okay

00:43:14For

00:43:14We

00:43:15Problem

00:43:16That

00:43:16Alone

00:43:16Is

00:43:16Make

00:43:17Job

00:43:17Description

00:43:18Good

00:43:18We

00:43:19Need

00:43:19AI

00:43:20For

00:43:20What are you doing

00:43:21For

00:43:22What

00:43:24The title

00:43:25So

00:43:25What

00:43:26This

00:43:27Finned

00:43:27Use

00:43:27Later

00:43:28So

00:43:28Prom

00:43:28Also

00:43:29The problem is

00:43:29Keep going

00:43:30Qualifications

00:43:33New

00:43:34We

00:43:34Onboard

00:43:35AI

00:43:35To

00:43:35Team

00:43:35Come back

00:43:36Before

00:43:36Come here

00:43:37If

00:43:38We

00:43:38Want to

00:43:39Make

00:43:39Job

00:43:40Description

00:43:40Good

00:43:41That

00:43:41The trick

00:43:41Is

00:43:42We

00:43:42Search

00:43:42Before

00:43:43In

00:43:43For example

00:43:44Kayak

00:43:44Let's

00:43:45Say

00:43:45What

00:43:45Yes

00:43:49Indeed

00:43:51This

00:43:52Site

00:43:53Job

00:43:53Guar

00:43:53We

00:43:54For example

00:43:55Search

00:43:55Kayak

00:43:55Let's

00:43:56Say

00:43:59For example

00:44:00We

00:44:00Youtube

00:44:01Specialist

00:44:09We

00:44:09Search

00:44:10Job

00:44:10Description

00:44:11What

00:44:13Artist

00:44:14Specialist

00:44:14We need a story

00:44:15If we can take a few

00:44:16Roll of footage

00:44:17And graphic

00:44:18No compelling

00:44:18Video

00:44:19Vlog

00:44:19Or podcast

00:44:25We're looking for creative and detail oriented

00:44:28We can really learn

00:44:31From the job description well

00:44:32For example, we can see

00:44:34If I also prefer, for example, it looks like this

00:44:40Densu

00:44:40For example

00:44:42Or

00:44:43WBP

00:44:44Agency

00:44:52If for example this is creative waste, yes

00:44:54We

00:44:55The trick is

00:44:56Make a prom

00:44:57Good

00:44:57Let's find out first

00:45:00Kayak

00:45:03Cater Explorer

00:45:04Let's see how they make job descriptions

00:45:09For example, we are talking about a media planning manager.

00:45:11Let's see

00:45:12How does he write media planning?

00:45:20You will manage integrative media and communications

00:45:24Lalalalalalalalalalalala

00:45:25That's it

00:45:25Kayak

00:45:26World account

00:45:27Keep going like this

00:45:27Key responsibilities

00:45:29Champion and planning

00:45:30We will be checking this

00:45:31Which one do we need?

00:45:32Which one doesn't?

00:45:32We take out what we need

00:45:35He added that we need it

00:45:37That's how we make it known

00:45:39Like for example

00:45:39Oh

00:45:40I think I need AI

00:45:41Make me a website

00:45:43But I don't understand

00:45:44Coding from where

00:45:45That means we need AI

00:45:47Make us code, please

00:45:48Recruit the AI, please

00:45:49The method

00:45:50The way is

00:45:50Make

00:45:51Kind of like prom at first

00:45:53That's it

00:45:53The AI needs it

00:45:55What kind of person to be

00:45:57The way is to find out

00:45:58For example, kayaking

00:45:59If we want to look for a software engineer

00:46:00Let's say company

00:46:02Create a software engineer

00:46:03Let's say Google

00:46:04Google

00:46:05Google

00:46:05Car

00:46:05Google

00:46:17Software engineer

00:46:22Here

00:46:27Until it's clear

00:46:27Google software engineer

00:46:28Develop the next

00:46:29технологiliar

00:46:30Change

00:46:30How billions of users connect

00:46:31Blame

00:46:32Blabi

00:46:33Blah

00:46:34BYUco

00:46:34Ben

00:46:34Building

00:46:35secure AI product That

00:46:37million Will

00:46:38Trust Responsibility

00:46:41All

00:46:42like this Nah

00:46:42We are like

00:46:43Oh, you know that

00:46:44It means

00:46:44What does this mean?

00:46:45what is it? This is very useful

00:46:46For friends

00:46:47the questioner

00:46:47the one that can

00:46:50use AI for

00:46:53many roles

00:46:54but we are

00:46:55My friends don't know what this term is

00:46:58I need a way to do it

00:47:00later we will be like copy paste

00:47:02this to AI

00:47:02keep going like this

00:47:05for example, we copy it, yes

00:47:07keep going like this

00:47:08this is paint

00:47:09O

00:47:13looking for

00:47:14creating a meta

00:47:16from AI

00:47:19to help me

00:47:20develop software

00:47:26this is

00:47:36Well this is a good AI

00:47:37I like the cloud because

00:47:38he could have asked us first

00:47:40what kind of software do you

00:47:42mainly want to help with

00:47:44well this is like

00:47:44backend front end

00:47:46for example

00:47:48what should they prioritize

00:47:54code quality

00:48:03make it

00:48:05there are a lot, right?

00:48:09This

00:48:09how we hack

00:48:11let us know what the reference is

00:48:13then like we can post-check too

00:48:14like Google

00:48:16Google

00:48:17career

00:48:19jobs

00:48:21agree

00:48:38so this

00:48:39so like

00:48:39if we

00:48:39copying Google

00:48:41he's heavy on security and compliance

00:48:42so if for example

00:48:44we will need something like security first thinking

00:48:48scale

00:48:48the scale is big

00:48:50the scale is big

00:48:52so if for example

00:48:54this is for mid-level

00:48:54Okay

00:48:55if staff level

00:48:58maybe it's still okay too

00:48:59like that

00:49:00so we can

00:49:01have nuance

00:49:01we can chat

00:49:03that's the trick

00:49:07onboard AI to the team

00:49:08how do we do it

00:49:09onboard AI to the team

00:49:11this is the secret of AI

00:49:12it's easier to understand us

00:49:13So

00:49:16I said earlier

00:49:17like oh there's this prompt

00:49:18there is this prompt

00:49:19all sorts of things like that

00:49:19we can have

00:49:21how to

00:49:22That AI

00:49:24always understand

00:49:25what we want

00:49:26by making

00:49:27his name

00:49:27all sorts of things

00:49:29the name of the project

00:49:29if in many places

00:49:30if in

00:49:32CGPT is the name of the project

00:49:33in the cloud it's called a project

00:49:34in this gem the name is

00:49:35gem

00:49:37jam

00:49:38in cloud pilot its name

00:49:39agent

00:49:41again all the names

00:49:42actually similar

00:49:44so if for example in

00:49:45CGPT this projects

00:49:47keep going like this

00:49:48there will be components

00:49:49the projects

00:49:50keep going like us

00:49:51put this in

00:49:52what is this instruction

00:49:53keep going like there is

00:49:53what are the project files

00:49:54then we stay

00:49:55chat

00:49:57if in another AI

00:49:59The same

00:50:00I try

00:50:02model in

00:50:02this is it

00:50:04projects

00:50:07I have never made a project

00:50:08for

00:50:09this account

00:50:10because it's a new account

00:50:11for example we make like

00:50:13let's say what yeah

00:50:15let's say kayak

00:50:19emergency

00:50:20plan

00:50:24hormones

00:50:28how to create

00:50:30emergency plan

00:50:55for individual

00:50:58v2

00:51:03that's a very good word

00:51:05Hi

00:51:06can you help me

00:51:08gather

00:51:09files

00:51:10for

00:51:12this

00:51:12project

00:51:13Hi

00:51:16Hi

00:51:20Hi

00:51:28emergency

00:51:29emergency plan

00:51:31because of

00:51:32w3

00:51:33hormones

00:51:34so

00:51:35everything in this project

00:51:37it will be

00:51:39tells the story of

00:51:40One

00:51:41case only

00:51:43just about this

00:51:45for example I make

00:51:46kayak about

00:51:47hormus here

00:51:47kayak

00:51:48personal

00:51:53gather

00:51:57personal plan

00:51:59or family plan

00:52:00for

00:52:01emergency

00:52:01For

00:52:03this hormone

00:52:04I think I want to know

00:52:06what do I prepare?

00:52:10So

00:52:11We can

00:52:13here

00:52:20there you go

00:52:21more or less the same right

00:52:22which will

00:52:23like a bandage

00:52:23panic buying

00:52:24rupiah

00:52:25LPG

00:52:26nickel

00:52:27nickel

00:52:28nickel

00:52:28well we

00:52:30use again

00:52:30come here

00:52:31we can make it

00:52:32custom instructions

00:52:34for example kayaking

00:52:35we make custom instructions

00:52:36here

00:52:38We

00:52:38clear

00:52:39Hey

00:52:40help me

00:52:41create

00:52:42custom

00:52:43instructions

00:52:44for

00:52:46cloud

00:52:47project

00:52:52so

00:52:54the

00:52:55project

00:52:56is

00:52:57emergency

00:52:58plan

00:52:59for

00:53:00my

00:53:01family

00:53:02during

00:53:03ww3

00:53:04hormones

00:53:08So

00:53:09he has

00:53:10kayak

00:53:10kind of

00:53:17context

00:53:18like that

00:53:19we are

00:53:21What

00:53:21who are we

00:53:22we are

00:53:23What do you want to do

00:53:28location

00:53:29Indonesia

00:53:32Jakarta

00:53:33Indonesia

00:53:34keep going

00:53:35put it back in

00:53:36number of

00:53:38adults

00:53:39I am five

00:53:40Keep going

00:53:42condition

00:53:43normal

00:53:47housing

00:53:48housing

00:53:50brand house

00:53:53vehicles

00:53:54one car

00:53:56one motorcycle

00:54:00all Indonesian

00:54:05passports

00:54:07then we make it again

00:54:09for example

00:54:09language

00:54:10spoken

00:54:12Indonesia

00:54:13English

00:54:14no dual

00:54:17passport

00:54:20budget

00:54:21preparation

00:54:23for example we enter

00:54:2410 million

00:54:29person

00:54:30supplies

00:54:31is

00:54:33none

00:54:52okay

00:54:54we will

00:55:05copy

00:55:06we copy

00:55:11come here

00:55:11you know

00:55:13Well, this is what it will be like

00:55:14the answer is different

00:55:15Hey

00:55:16hello

00:55:17do you

00:55:18understand

00:55:19my

00:55:20context

00:55:22context

00:55:32every time we chat

00:55:33whatever there is

00:55:34he will

00:55:35know right away

00:55:36who are we

00:55:36we are talking

00:55:37what are you doing

00:55:37and this is different

00:55:38same chat

00:55:39usually

00:55:39which exist in

00:55:41cloud

00:55:42usually

00:55:42or

00:55:42charging

00:55:43usually

00:55:43So

00:55:44this is next

00:55:44we have

00:55:46specific employees

00:55:47in

00:55:47this case

00:55:48only

00:55:52to large

00:55:54Aqua

00:55:56galley

00:55:57current case

00:55:59digital

00:56:00same case

00:56:02on line

00:56:02completely new

00:56:04sorry

00:56:11here

00:56:12we have a trigger

00:56:14this is interesting

00:56:15I myself

00:56:16because

00:56:16made

00:56:17like this

00:56:17this is what it seems

00:56:17very

00:56:18seen

00:56:18make now

00:56:19for example

00:56:20trigger

00:56:20signal

00:56:20to watch

00:56:22for example, if

00:56:23price

00:56:24crude oil brand

00:56:25on

00:56:26110 barrel

00:56:27USD

00:56:28on

00:56:2917 thousand

00:56:31Pertalite

00:56:32queue

00:56:33already up there

00:56:3330 minutes

00:56:35Pertamina

00:56:35I already told you

00:56:36kayak allocation

00:56:37adjustment

00:56:39Indomaret

00:56:40it's started

00:56:40finished

00:56:41oil

00:56:41with rice

00:56:42Bay statement

00:56:43I already told you

00:56:44like capital

00:56:44low restriction

00:56:45max

00:56:46withdraw

00:56:47FTM

00:56:48This

00:56:48for friends

00:56:49which has not been

00:56:50know

00:56:51this is it

00:56:51starting to be limited

00:56:52create currency

00:56:53foreign

00:56:53so we

00:56:54need to prepare

00:56:55flood

00:56:56forecast

00:56:57BMKG

00:57:01we need to have

00:57:033 Aqua Gaunts

00:57:04refillable

00:57:0520 thousand

00:57:0560 thousand

00:57:07keep going like this

00:57:07plastic indergan

00:57:08water proliferation

00:57:10proliferation

00:57:10tablets

00:57:11Oh yes

00:57:13make sense too

00:57:15keep on food

00:57:17rice

00:57:18oil

00:57:19Indomie

00:57:19sugar

00:57:20salt

00:57:21seminal nuts

00:57:21salt

00:57:22tuna

00:57:22I already have it

00:57:25peanuts

00:57:26mung beans

00:57:27medical

00:57:28basic

00:57:29oralid

00:57:29betadine

00:57:30face mask

00:57:31sanitizer

00:57:33flashlight

00:57:34candle

00:57:35power bank

00:57:37document

00:57:38polo copy

00:57:38ID card

00:57:39all kinds

00:57:41Already

00:57:41cash

00:57:43Well, this is it

00:57:45This

00:57:45so as if

00:57:46if we

00:57:47move again

00:57:51all the chats are here

00:57:52so it's different from the same

00:57:53normal chat here

00:57:54and we stay

00:57:55kayak

00:57:56Hey

00:57:56do you think

00:57:58I should

00:57:59find

00:58:01find

00:58:02new

00:58:02site

00:58:03so

00:58:08so if for example like

00:58:09oh we want to chat

00:58:10question

00:58:11our emergency plan

00:58:17just thinking

00:58:18that

00:58:19my

00:58:20income

00:58:21will

00:58:22be

00:58:23reduced

00:58:24that's

00:58:26kind

00:58:28what you can

00:58:29see

00:58:29right

00:58:51For example, we just want to chat

00:58:53we can use this

00:58:54So this is quite interesting

00:58:55its features

00:59:04what kind of skills

00:59:05what skills do we have

00:59:07Well, this is it

00:59:07quite practical

00:59:09what skills do we have

00:59:10like an office

00:59:11corporate

00:59:11exactly me

00:59:13I have

00:59:16IT

00:59:18digital marketing

00:59:23web development

00:59:25web app development

00:59:32content

00:59:33content creator

00:59:36for example

00:59:37for example

00:59:38how much

00:59:41evening on with this

00:59:42what kind of income

00:59:44you're looking for

00:59:45quick cash

00:59:49great profile

00:59:51you have high demand

00:59:51skills

00:59:52for example kayaking

00:59:53on local platform

00:59:55Google Ad Setup

00:59:58content writing

00:59:59short form video editing

01:00:01this is like

01:00:02more difficult but

01:00:03many need

01:00:04teach digital marketing

01:00:06for example kayaking

01:00:07in USD

01:00:09it's like

01:00:10we can have

01:00:12many contexts in

01:00:13this one chat

01:00:13Okay

01:00:15so this is our way

01:00:16make on board

01:00:17approximately we

01:00:18who are we

01:00:18because he will

01:00:19who are we

01:00:20save this

01:00:23context

01:00:24for the future

01:00:32oh there is

01:00:33oh memory

01:00:35memory will be the

01:00:39memory

01:00:48okay

01:00:57just turn on

01:00:58memory

01:01:09or the manual way is

01:01:13We can

01:01:15put this in here

01:01:17kayak

01:01:22help me update

01:01:25the custom instruction

01:01:30with the new context

01:01:33why do i prefer it like this

01:01:35because sometimes

01:01:37memory is not very reliable

01:01:39So

01:01:40if the work is really very important

01:01:42I always save

01:01:47the context is in text form

01:01:49that I can remember

01:01:52give it to me

01:02:00I will save manually

01:02:04so we have more control over what

01:02:07I remember and what I remember

01:02:10so we'll just save it

01:02:14Okay

01:02:28here

01:02:29we're back here

01:02:30we give instructions

01:02:32we copy

01:02:33well we can

01:02:35share too

01:02:36like that

01:02:37oh

01:02:38must go to the team

01:02:39it can be shared

01:02:40Now

01:02:41really playful

01:02:41well we can

01:02:43do a lot of things

01:02:44with this

01:02:45so we can make it

01:02:46I like

01:02:46one cloud

01:02:47create a project

01:02:48for example finance

01:02:50one for what

01:02:51one for what

01:02:51this is one way for us

01:02:53like having a lot of employees

01:02:55like that

01:02:56we're back again

01:02:58Now

01:02:58this is an example

01:02:59customer instructions

01:03:00earlier

01:03:01we used it earlier

01:03:04emergency planner

01:03:05Well, this is for you

01:03:07coach

01:03:07like that

01:03:08I'm a role at

01:03:09blah blah blah blah blah

01:03:10you are my expert

01:03:11coach and advisor

01:03:12assisting

01:03:12and proactively coaching me

01:03:14in my role

01:03:15to reach maximum potential

01:03:16I will provide you with detailed information

01:03:18about our company

01:03:19blah blah blah blah

01:03:20I expect you to

01:03:21ask me a question

01:03:23important missing information

01:03:25and challenge

01:03:26challenge my assumption

01:03:27ask me a question

01:03:28that will

01:03:29let you

01:03:30most effective

01:03:34that will let you

01:03:35most effectively

01:03:36coach and assist me

01:03:37in my role

01:03:38in coaching me

01:03:39to blah blah blah

01:03:39so like

01:03:40we are like

01:03:41still know

01:03:42eh

01:03:42I'm like this, you know

01:03:43You're like this

01:03:46So

01:03:47Friends, you can try it, okay?

01:03:48if you want to test

01:03:49This program is ready to use

01:03:50screenshot

01:03:51just give it like

01:03:51The AI

01:03:52The AI understands

01:03:54So

01:03:55We can

01:03:56mertes like that

01:03:58in this case we have

01:03:59one employee

01:04:00our coach

01:04:02well we're just like

01:04:03kick off with AI

01:04:07Now

01:04:08the easiest way

01:04:09For

01:04:11start

01:04:12kick off project

01:04:13It is

01:04:16We

01:04:17just chat

01:04:18know that you had

01:04:19the context of my company

01:04:20and my team

01:04:22I would

01:04:22tell you a bit about

01:04:23my initiative

01:04:24that we're working on

01:04:25blah blah blah blah blah

01:04:26so like

01:04:27give some initial context

01:04:29so we'll let you know

01:04:30what we know

01:04:31against that

01:04:31for example we start

01:04:34let's say like here

01:04:35now that

01:04:37you know

01:04:38my context

01:04:41on my situation

01:04:43it's us

01:04:44personal yeah

01:04:45not until this, yeah

01:04:46we make

01:04:47we make

01:04:48opus

01:04:48if you want to plan

01:04:49planning

01:04:49we will opus

01:04:52I want to start

01:04:54I want to start this

01:04:55initiative

01:05:05before

01:05:05before starting

01:05:06This

01:05:07usually this

01:05:08my habit

01:05:08do you have

01:05:10any

01:05:11question

01:05:12for me

01:05:18this is my habit

01:05:20probably because

01:05:20always teach yeah

01:05:21like I asked before

01:05:22he needs

01:05:22who asked you

01:05:28load

01:05:30free

01:05:33I have

01:05:35a small

01:05:36gas

01:05:38stove

01:05:45three

01:05:49pump

01:05:55four

01:05:56pentam

01:05:57max

01:05:59five

01:06:00in

01:06:01Jakarta

01:06:03six

01:06:04no

01:06:05seven

01:06:07single

01:06:07bank

01:06:08which ya

01:06:10this is the data

01:06:11ptw

01:06:11fake yeah guys

01:06:12so don't

01:06:12Don't

01:06:13I think so

01:06:14is it really like this?

01:06:15I just have to fill it in

01:06:16mandri

01:06:17bandri

01:06:18for example kayaking

01:06:183 miles

01:06:21comment

01:06:22sociology

01:06:23sorry

01:06:24for example

01:06:2510

01:06:26no

01:06:43that

01:06:44he will

01:06:45ask again

01:06:46no even

01:06:49office

01:06:50gas

01:06:50small

01:06:51camping

01:06:56I just

01:06:58for table

01:07:06that's

01:07:08only

01:07:08me

01:07:09working

01:07:10for example

01:07:10i

01:07:25he will

01:07:26think

01:07:26he will

01:07:27look

01:07:27oh

01:07:27this much steel

01:07:28he needs

01:07:28this much

01:07:29he needs

01:07:30cdfg expert

01:07:31it's already started

01:07:31start

01:07:33The AI is already there

01:07:34start to know

01:07:35what is our condition

01:07:36compared to kayaking

01:07:36for example

01:07:37Hey, please make it for us

01:07:38emergency plan or something

01:07:39it would be too wide

01:07:40so for example here

01:07:41we start kickoff

01:07:42with love

01:07:43what do we need

01:07:44or if

01:07:45my way is

01:07:47we ask

01:07:48The AI asked

01:07:48what other info does he need?

01:07:49and we direct

01:07:50you need to know

01:07:51this too

01:07:52you need to know

01:07:52this too

01:07:52so like

01:07:54you know

01:07:55if for example in

01:07:55onboarding right

01:07:56it's a bit

01:07:59sad yeah

01:08:00if for example we

01:08:00only in one direction

01:08:01meaning like for example

01:08:03the ideal is

01:08:03we can be like

01:08:05there are two directions

01:08:06Where

01:08:06one said

01:08:07pan

01:08:08and the one who came back

01:08:09eh no

01:08:09you mean

01:08:10typing here

01:08:10eh no

01:08:11come here like that

01:08:11So

01:08:13interactive like that

01:08:15Now

01:08:15my reference is also possible

01:08:16if friends

01:08:17lazy to type

01:08:18can speak

01:08:19here

01:08:20this can't be done

01:08:21because of that

01:08:22but friends can talk

01:08:23on the cellphone you can also talk

01:08:25eh

01:08:26delicious

01:08:27if friends can use it

01:08:28English

01:08:28can't

01:08:29check again

01:08:29English is better

01:08:31if friends can talk

01:08:32So

01:08:32learn

01:08:33English

01:08:34don't do it little by little

01:08:36ngenyir content

01:08:37to English

01:08:38yes

01:08:40just working with AI

01:08:41before that we

01:08:42check the plan first

01:08:45long too

01:08:53friends can

01:09:07enjoy!

01:09:40enjoy!

01:09:55enjoy!

01:10:25enjoy!

01:10:33enjoy!

01:10:36enjoy!

01:11:06enjoy!

01:11:34enjoy!

01:11:53enjoy!

01:12:04enjoy!

01:12:12enjoy!

01:12:14enjoy!

01:12:16enjoy!

01:12:20enjoy!

01:12:55enjoy!

01:12:58enjoy!

01:13:09enjoy!

01:13:11enjoy!

01:13:13enjoy!

01:13:34enjoy!

01:13:36enjoy!

01:13:46enjoy!

01:13:48enjoy!

01:13:49enjoy!

01:13:51enjoy!

01:13:54enjoy!

01:13:56enjoy!

01:13:59enjoy!

01:14:00Steps, making an outline, writing one section at a time, reviewing the article.

01:14:05Examples are, for example, what is the writing style like, what is the target audience like, what is the example piece like, okay?

01:14:11Well, that's all.

01:14:13Do we need a long promenade? Ideally, this is it.

01:14:19We can't assume that AI is like humans, right?

01:14:21how the more often we work with him, the more he remembers us.

01:14:24I personally feel that this is a different problem for different people.

01:14:27I myself feel, I still want a long promenade, not because it is a necessity,

01:14:36but this is an exercise for me, because I feel, I am getting stupider the shorter the prome is.

01:14:43I have to, I have to use my brain to think.

01:14:45Because if I proclaim too easily, sometimes I really feel like I'm just not using my brain.

01:14:52And the results are glistening, usually.

01:14:54So, this is connected to the mindset of working with AI, right?

01:14:58This is one person who made Warren Buffett Metaprom.

01:15:02It's really long, there are parts, this is up to part 9, part 12, part 12 is right.

01:15:10So, I've broken this down point by point, but the original is longer, like around 5,000 characters.

01:15:15I once shared it on Discord, learning GPT.

01:15:17If you guys want to check, you can check there.

01:15:21This metaprom shows that when we make a decision, the more senior the person, the cooler the person, the longer it will be.

01:15:27Why?

01:15:28Writing prom isn't just writing, it's deciding.

01:15:31If friends have the ability to think or not.

01:15:34Do you have any sense?

01:15:37It looks like it.

01:15:38People who just make things as they please, carelessly, but also make them with intention, seriously.

01:15:44I said this to my team yesterday.

01:15:48In the AI era, making products is much easier now.

01:15:52Why?

01:15:53Because the entry is very easy.

01:15:56Imagine, for example, there is a machine that is cheap.

01:16:02And he can create any food.

01:16:04Or for example, do you know where there used to be a dream machine?

01:16:08All drinks are in the form of water, right?

01:16:12So like, so make juice.

01:16:14The juice is available, we just have to choose.

01:16:16I want Coca-Cola, I want Sprite, I want whatever, and so on.

01:16:20Just click, it will come out.

01:16:22Because you just have to combine the chemicals.

01:16:24And imagine, that juice machine is sold to everyone.

01:16:28Everyone can buy it.

01:16:30Everyone is starting a business.

01:16:33What happened?

01:16:34What will happen is, everyone can start a business.

01:16:37Everyone will make a business.

01:16:40But, the difference is the quality,

01:16:43level of service, intention, cleanliness.

01:16:48The same thing is happening now.

01:16:50Everyone can use AI.

01:16:51Everyone can do anything using AI.

01:16:55Can.

01:16:57But, there are also many who are crazy.

01:16:59Why?

01:17:00No intention.

01:17:02Metaprom is long, you know.

01:17:04I made that prom, we're for Youtube, okay?

01:17:06I once shared, the origin of version 5, version 6.

01:17:09But I never shared version 7 again.

01:17:11Why is the metaprom so long?

01:17:12It's like our lifeline.

01:17:14So, it's like a pulse.

01:17:16And that's not a sign of stupidity.

01:17:21But it shows that we use it often.

01:17:22Well, we always fix it, always fix it, actually.

01:17:25If you guys know, in learning GPT we have one module.

01:17:29Here I am showcasing a little bit about learning GPT Pro.

01:17:31We have a special module to correct the role of humans in prom.

01:17:39Then we also have like, how to fine-tune the prom.

01:17:45So, what I believe is, we can definitely make a prom.

01:17:52So, and you have to be able to make it yourself.

01:17:54Because our main task is only two things.

01:17:56We don't want to read yet.

01:17:58Actually we want to write.

01:18:01If we don't want to read, we don't want to write.

01:18:03Sorry.

01:18:06First, friends can look for the coastline.

01:18:08Which might be more suitable.

01:18:09Maybe those who don't want to read and write.

01:18:12It's just really automatic.

01:18:13That's not up to us.

01:18:16And I guess, what are you doing?

01:18:18Alive huh?

01:18:19If we just really automate everything.

01:18:22That.

01:18:23That's what I believe.

01:18:25This is Metaprom for Buffet stalls.

01:18:27I've used it, the results are okay.

01:18:30But I'm still not sure what this whole time is about.

01:18:33Okay, because this is someone's prom.

01:18:34I want to make my own prom.

01:18:37So, does it need context?

01:18:40Why do I need to explain this throughout Eid?

01:18:45With context.

01:18:46Onboarding will take longer.

01:18:47We seem to work longer hours.

01:18:49We seem to have been around for a while longer.

01:18:51But the work is much more consistent.

01:18:53The results are much more consistent.

01:18:55The quality is much more consistent.

01:18:57The impact is,

01:19:00we don't need a more detailed prom.

01:19:01While working.

01:19:03Without context.

01:19:04We will explain it many times.

01:19:07We sometimes forget the details.

01:19:09We're going to need a lot of copy-pasting.

01:19:13So, more or less like that.

01:19:16So, no matter how smart AI is.

01:19:20There is still a chance of being wrong.

01:19:22Our job is to be good managers.

01:19:25Who wants to explain.

01:19:27Read.

01:19:28And want to give feedback.

01:19:29For friends who have worked in an office.

01:19:31Or still working in the office.

01:19:33You know there are good managers and bad managers.

01:19:35A good manager is like,

01:19:37we were told what our job was.

01:19:39We should be like this, we should be like that.

01:19:42He read our work.

01:19:43He gave us feedback.

01:19:46I'm still in the process.

01:19:49Managing people and managing AI.

01:19:52But I know.

01:19:54If I want to explain,

01:19:56want to read and want to give feedback.

01:19:57Usually the results will be good.

01:19:59Most people don't want this process.

01:20:02So, it's as if everything is instant.

01:20:05You are the one who understands me.

01:20:06It's not me who understands me.

01:20:08Well, a process like that is not possible.

01:20:10Unless your friends have a very large budget

01:20:12and the tokens are very wasteful.

01:20:15So, again, I want to tokenin approx

01:20:19Friends, just choose.

01:20:20Which path do you want to take?

01:20:22This material is about an hour long.

01:20:24Hopefully friends,

01:20:25Remember, we have a gentleman's agreement.

01:20:27If friends have arrived here

01:20:29and friends feel useful,

01:20:31I only ask for one,

01:20:32just subscribe to this channel.

01:20:34Help so more people can see this video.

01:20:37Because I share this video for free.

01:20:39The goal is very simple.

01:20:40Lots of sales

01:20:42and claims to be an AI expert.

01:20:46I think they

01:20:48just doing it for the sake of money.

01:20:51I mean, I also make,

01:20:52I make businesses,

01:20:54I sell classes.

01:20:54But, I think there's something bigger than that.

01:20:58I truly believe that

01:21:01the time of AI will come

01:21:04will really make mass THK

01:21:06to everyone

01:21:07and at that time

01:21:09everyone needs to learn AI.

01:21:11And I hope this video

01:21:13or learn GPT

01:21:15can help

01:21:17friends

01:21:21adaptation.

01:21:22And I don't want to just adapt.

01:21:24I want to be good at it.

01:21:26I want to jump.

01:21:29So,

01:21:31like that,

01:21:32for friends who are still interested

01:21:33same as learning GPT,

01:21:36I have

01:21:38special programs.

01:21:42This method is a bit manual, yes.

01:21:44But,

01:21:44friends just check it out

01:21:45on the website there is

01:21:46like a small button

01:21:48below right

01:21:48WhatsApp

01:21:49or friends click down.

01:21:51Here.

01:21:52There is WhatsApp.

01:21:53Well, click on this.

01:21:55Later

01:21:55talk to my CS.

01:21:58I will give you a promo

01:21:59special

01:22:00for people who watch

01:22:01until

01:22:02O'clock

01:22:02this is it,

01:22:04an hour

01:22:0421 minutes now.

01:22:06Just click this below.

01:22:08I don't know later

01:22:08like sometimes

01:22:09the number

01:22:09sometimes we change our numbers

01:22:11all kinds.

01:22:12But,

01:22:12must be there

01:22:13WhatsApp.

01:22:15And it's here too.

01:22:17Now,

01:22:19just paint it to my CS.

01:22:20We have one full time CS

01:22:21who helps friends.

01:22:23Just say promo.

01:22:25I've watched the video

01:22:26YouTube

01:22:27more than an hour

01:22:27and if he says

01:22:29there is a promo.

01:22:30I will help

01:22:31friends

01:22:31who want to learn.

01:22:33We have several courses.

01:22:34Now we are again

01:22:35there is a course for

01:22:36learn GPT Pro

01:22:37which is not yet from 0

01:22:39until you become an AI expert

01:22:39it learns everything

01:22:40while Excel.

01:22:43We will make it

01:22:44some more courses.

01:22:45For example, if

01:22:45any suggestions are welcome.

01:22:47I'll check first.

01:22:48I think next

01:22:48it's done.

01:22:50Now,

01:22:50just Q&A.

01:22:52The Q&A is simple.

01:22:53Friends stay

01:22:54pass in the comments column.

01:22:55the way to do it is to subscribe.

01:22:57So how will it be later

01:22:58will check

01:22:58Have you subscribed or not?

01:22:59If you have subscribed

01:23:00I will reply

01:23:00direct questions.

01:23:01But I want to

01:23:02the question is quite deep, yes.

01:23:03Don't tell me it's just like that

01:23:04eh which one is good.

01:23:06Is this good or not?

01:23:07Is this good or not?

01:23:08So,

01:23:08please write a question

01:23:09in the comments column

01:23:10on this YouTube.

01:23:11The good one

01:23:13I will reply.

01:23:15Okay?

01:23:17That's all for now.

01:23:17do not forget

01:23:19heart

01:23:20our agreement, okay?

01:23:22Keep going

01:23:23see you

01:23:24next video

01:23:25on the channel.

01:23:26Bye bye.

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