Ultimate AI Masterclass for Founders and Executives 💰| Vaibhav Sisinty | IBP EP28

Category: AI Trends

Tags: AIAutomationRecessionToolsWorkforce

Entities: AmazonArtician AIChatGPTChinaClaudeDonald TrumpGoogleGrowth SchoolIndiaLindy AIMicrosoftNvidiaODOOpenAISam AltmanUSY Combinator

Transcript

00:00

Sam Altman in the beginning of the year kind of said that AI agents will enter the workforce this year. This year I expect that in 2025 we will have systems that people look at like what agents are the thing everyone is talking about.

I

00:15

think for good reason. Open AAI just announcing an improved model their AI model.

They say it has better reasoning. Open AI has got the wind at its back.

I think India should be doing everything. I think India should be one of the leaders of the AI revolution.

So I can do this without knowing anything about

00:31

coding. I don't know how to code but I know how to build a product.

I managed to kind of raise $5 million. Hi folks, my name is Rebendi the founder Gone School Mr.

Webhub. Growth school is where we make you become top 1% professional/founders.

And today where does growth school stand? I think we've

00:47

grown 10x the company that started as four five people right now has 150 plus people. Wow.

Last month we had learners from 45 different countries. 45 different countries.

We are the smallest of all the startups. We also have the least amount of funding of all the startups.

A LinkedIn top startup family

01:02

of 300,000 learners. Amazon has already laid off 14,000 people.

Google has already laid off people. And we're seeing this all across the tech industry.

As a working professional, what exactly am I supposed to do? Microsoft has laid off people

01:17

across multiple divisions. 150,000 tech workers have been laid off.

of Meta, Amazon and others have frozen hiring Amazon today announcing it's going to cut 18,000 workers in this for every problem right there are tools for it one

01:34

great place for you to find tools for your problem is there's a website called as if a working professional is watching this episode right now what are the first three steps that they're supposed to take in order to make themselves super efficient I believe that everybody has to become something called as an AI

01:51

journalist And there are just so many people I feel so sorry, so sad for them that they are so stupid that they think AI is all about chubby. If you have read the news, Donald Trump is making it impossible for a lot of countries to buy GPUs.

Trump

02:08

and his team are planning to expand efforts to limit China's tech advancements in pressuring allies to also get in line. We are 6 months to one year away from almost all the code to be written by AI.

All boss the future programming language is not Python is

02:24

not Rust is not JavaScript [Music]

02:41

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Hi Weber,

04:18

welcome to the Indian business podcast. It's been a long time since you wanted to have you and finally you're here and uh guys just to give you context I have a confession to make.

About a few days back I was having a conversation with web and I told him that yeah bro we use a lot of AI. So he's like yeah that's

04:34

amazing. And then he started talking and then I realized that um I am an AI illiterate.

I don't know how to use AI well and I'm an amateur. Weber, you stand at a very very interesting juncture.

On one side, you are at the cutting edge of education. On the other side, you are at the cutting edge of technology.

You teach AI now just like

04:51

you used to teach LinkedIn and you are super bullish about it. And like I said, I've been speaking to you and it has been life-changing for me.

I don't use these terms very loosely, but I can say that whatever you've told me about AI and about systems and processes, that has been life-changing. And the beauty

05:06

is I spoke to you after I spoke to Ranir and Reanir said, "Bro, content is not your mode. systems and processes are your mode.

And then while I was trying to build those systems and processes, I spoke to you and then it was life-changing because I learned how to build those systems and processes at 10x

05:23

speed with 100x more efficiency. But now I want to understand how does it apply to the working professionals of the world today?

Because the US recession is real. We're expecting recession in the next 3 to four months.

There is already panic in the market and now everybody's supposed

05:39

to rethink their position in their own companies. Amazon has already laid off 14,000 people.

Google has already laid off people and we're seeing this all across the tech industry. And we're expecting that once US sees a recession, even the Indian tech industry is going to see a recession.

So my question is as

05:56

a working professional, what exactly am I supposed to do? Let's break it down, right?

There are multiple aspects to this. One is what happens when a recession arrives?

The spending power goes down. When spending power of a consumer goes

06:12

down, what are the biggest companies out there in the US? They're either tech companies or consumer companies, right?

Essentially, uh, deep tech companies or consumer tech companies, right? And they all rely on some level of spending from the consumers.

When the consumers goes

06:29

down, when the consumer spending comes down, the appetite for a company to spend on their people directly and indirectly goes down. When that happens, that leads to layoffs.

Right? Now, in this case, right, we are in this very interesting time when there's a

06:45

recession because of multiple geopolitical aspects which I don't want to get into. While that recession is happening, it becomes a very good reason for people for the companies to adopt a process which is super future-paced and super efficient.

What I'll tell you what

07:00

I mean by that. There is this massive rise of AI agents that is happening.

Uh I don't know if you've seen this. Sam Alman in the beginning of the year kind of said that AI agents will enter the workforce this year.

This year what does

07:16

he even mean by that? If you break that down, right?

Essentially every one of us have used chat GPT Gemini and all those tools right and we think we know all about AI just like me right the problem is that there is a gap in understanding

07:31

what AI is capable of what you're seeing as an assistant where you ask a question and you get an answer and that is where it stops as a result you like oh this is cool I asked for a poem for my dog and it gave a poem cool right AI is cool but the real power of AI today as we live is that it has the ability

07:48

to complete a full task on your behalf. You were just talking about operator.

What does an operator do? An operator can use computer on your behalf.

For example, a few days back, right? I wanted to get a bunch of ideas on companies that I could probably work on

08:06

and the best place for me to get these ideas was Y Combinator. So essentially the problem statement was I had to go through 5,000 companies data uh and I had to read each one of them check out each one of their websites to see if there is something that I can build like

08:21

this in India with my expertise that's a lot of context things that I'm good at the audience that I have the ideas that Y cominator has bagged and can I do it in India right a lot of context had to do it manually chat GPT or tools like

08:36

this cannot do it out of the box because it cannot pull in so much context cannot do things and I want all of this data on a Google sheet to be filled. Operator is a great use case for this.

So I went to chat GP operator gave a very nice prompt uh explaining what I exactly want. Left

08:51

it 9 hours later came back with around I think 25 26 companies that I should look at out of 5,000. Wow.

After 9 hours. Yeah.

I mean it took I don't remember. Overnight I left it.

Okay. Right.

Only place where I had to be part of it. It

09:06

could be done in like 50 minutes or so. I don't know.

Overnight I left it and passed out. Only place I had to intervene was I had to log into my Gmail account.

It tells you I don't have access to your Gmail. Please log in.

So I logged into my Gmail account so it can create a Google sheet and that's all I did. I I left my computer passed out.

I

09:24

got 25 startup ideas because it was simple task. AI was able to do it or operator was able to do it.

What does operator do? This if I if I had if I wanted a human to do it, right, it's a easy 10day job.

H right and it needs a

09:40

human to do it. But now AI is AI agent is able to this is what an AI agent is.

A assistant cannot do this. Assistant can you can ask a question to the assistant it can give you an answer.

It cannot accomplish a task but an AI agent can. This is an AI these are the kind of AI agents.

For example chat GPD has

09:57

something called as deep research. What does deep research do?

Just like a human being if you had to research on a topic what would you do? go out there, read hundreds of articles on the internet, make notes of this and all of that, right?

Like it takes a long process. Deep research does exactly that.

It

10:14

takes your command, breaks it down, goes and reads hundreds of articles on your behalf and comes back and comes back and gives you an output. That's an AI agent.

Agents like this are going to enter our workforce. And these AI agents, right,

10:30

are incredibly powerful already. and they're going to only get better, right?

And when these AI agents come in, companies have to find reasons to get rid of human beings and get these AI agents to work on their behalf because they can save so much money. Agents can

10:46

work 24/7. That is what AI operators can do in 24 hours.

In a few hours, I would not say 24 hours. I don't remember the exact number, but it accomplished it.

I don't care how long it took. If you get a human being to do the same thing, it's going to take five, six hours.

But the

11:01

crazy part of this is I was able to replace a human who would be like a you know entry level or like two three years experience basic understanding of startups person to do this job. Instead I could get an AI agent to do it overnight when I'm sleeping right this

11:18

is the part that people have to realize and this is what Sam Alman meant that AI agents are entering the workforce this year. There are going to be a lot of agents like this like deep research is a great agent which does research like a human being.

It when you give a question to it when you give a prompt to it

11:34

saying I want you to accomplish this it breaks down the task thinks like a human just like we do using something called as a reasoning model uh and I don't want to geek out that there's chain of thought reasoning that kicks in here. It breaks down the question, thinks like a human being, researches hundreds of

11:51

articles on your behalf and finally gives you a report in let's say 50 minutes, 60 minutes, sometimes a couple of hours, right? But that report would take you weeks if not days for you to do as a regular person.

Correct? The lot of agents like this which are entering.

For example, there are business development

12:07

agents which can do cold emailing on your behalf. All autonomous.

find email ids, send people email id, reply to people's email, everything it can do out of box. Can you give me the name of these tools?

So there is one tool that you can use called as

12:23

artician AI which is for SDRs or sales representatives. One more tool where you can build a few agents like this is Lindy AI which is very very no code.

Of course if you want to go a little geeky then you can go to N8N N8N or crew AI.

12:39

What do you mean geeky in a sense if you know how to write a little bit of code or not even know how to write code but if you're comfortable copy pasting code right because a lot of people look at code and like I can't do this boss I don't know how to write a code I don't I don't know how to write a single line of code I know how to control C andrl V do

12:56

that enough and what will help you chat GP will so the moral of the story is that all these working professionals are supposed to learn how to use operator no the moral of the story with the recession point that we're getting to right companies have window to replace humans with technology which is AI

13:13

agents and that is fundamentally why you will see a lot of these companies like Google and all right are kicking out middle managers senior managers because they are the most expensive human cost that a company can incur right and they have to get rid of it and replace that with as much of AI processes as possible

13:30

with recession coming in this is going to compound because there's a reason for a company to save money they also have a need to save money and they also O have a potential solution. The companies that are going to do very well even during recessions are probably the air companies like open AIs of the world,

13:46

Google's of the world while the rest of them are going to adopt it as fast as possible and hence the recession. In fact, this second line of thought right uh I'll come to the India aspect of it which you asked me.

I think India could be in a very soupy situation. Could be

14:01

or could not be. Uh there are two variations to it.

Again these are perspectives right? I don't know if you have come across this because you're talking about US, right?

Yeah. If you have read the news, Donald Trump is making it impossible for a lot of countries to buy GPUs from Nvidia,

14:19

right? And in fact, for China, he has completely banned it.

There are a lot of other countries have banned it as well. India comes in the level two where he allows us to buy some GPUs but not as many as we want.

And then level one can buy how many ever they want. Why do you think is the reason?

The primary reason

14:34

here is Donald Trump doesn't want these countries to build AI capabilities as good as the US capabilities. Now he'll be like yeah chat GPD to what is the problem?

Let other people build. Why is Donald Trump being so like uh you know

14:49

trying to hold all these GPUs and by the way FYI GPUs are the engine for these AI models to get trained on. So without GPUs there is no AI right?

So that is the hardware part of it. Why is he doing this?

Because I think he has seen

15:04

something that most of us have not. You see human capital the reason why US or countries expensive countries have to rely on countries like China, India and everywhere else is because the cost of human labor is so high there that making

15:19

an iPhone there end to end would cost the would cost basically 2x the cost of iPhone would 2x. So it won't make sense.

As a result they pass it on to countries where human labor is cheaper. Now with AI coming into the picture, there is intelligence coming in.

Machines are

15:36

becoming more intelligent than they ever were. Now with this technology, whoever controls this technology can control the whole supply chain to a point where you can build autonomous factories.

Boss, there is real estate in terms of space to set up factories. You

15:51

can set up a factory in desert also and there's a lot of desert. They can dig up a hole and put it underground also.

That space is not a problem. The problem is people are going to work in those factory.

But if there is a technology that is existent or that could be built where humans won't be

16:07

needed to build a factory or to run a factory then a country like us doesn't have to depend on a country like China to build their products. Correct.

Because the biggest arbitrage is the cost arbitrage. Yes.

And that is controlled with AI. So whoever builds that technology

16:23

first will control the power. So do you think Trump is trying to consolidate all the manufacturing powerhouse within the United States through AI?

I think so. I I that is how it looks like because I'm sure uh he has seen the dark factory videos.

Yeah, bro. Those dark factory

16:39

videos are just insane. Like I saw this video where there was barely any light.

Yes. And they're like why are there no lights in these factories?

Because there are no humans. There is no need of light.

because there are no humans and bro it

16:56

was mad like it was mindblowing now in fact Elon Musk even says that the cost of producing a model S is 65% cheaper in Shanghai than in the US which is why even though Trump has imposed tariffs

17:12

what he's essentially doing is punishing the consumers of America because he doesn't want them to buy Chinese goods problem that if there's a $1,000 iPhone It's not an uncle in Beijing who's going to pay another $100 for it. It is Karen

17:28

from New York who's going to pay another $100. And because of this, the US companies are helpless.

They cannot do anything because of two reasons. A, even if Chinese phones cost $1,100, they can't do anything about it

17:46

because their products cost on the upwards of $1,500. So, they can't do anything about it.

Number two is that they still have to buy raw materials from China and China in return has also imposed tariffs because of which raw materials have become expensive. So the

18:01

American products have become even more expensive. So tell me something.

I understand this whole vision of making America great again. But how does it make sense in the present day world?

And more importantly, how does it make sense for India? What are we supposed to do in

18:17

this drama between America and China? Yeah.

uh the tariffs reciprocal tariffs have not gone live yet right across the board and like we were discussing China doesn't have a lot of tariffs yet I think it's a bait card that Trump is using at this point of time right it

18:34

looks it looks like a great leverage point to have conversations with a lot of lot of countries right but I don't know if this will actually go through because it's a net net destroyer of economy then uh uh advantage right that's what economists say based on what

18:49

I Understand now where does India sit with this equation? What does India exports the most?

Software services, pharmaceuticals, auto parts, jewels, jewels, jewelry is number one, diamond. Yeah, d everything around gold, jewelry is number one,

19:05

pharmacy is number two, pharmaceuticals is number two. The third is IT.

The biggest of that is IT. No, no, it's not.

It's a third. It's not.

It's the third largest actually. It's third largest.

Yeah. In terms of exports globally, not just to us.

I'm talking about global. Okay.

Okay. Okay.

All right. Global exports not US exports.

I don't know of

19:22

US uh export numbers but it is major. Right.

Why were countries relying on India to export it? Cost arbitrage.

It always the whole world trades because of arbitrage. Correct.

The cost arbitrage

19:38

is that one engineer in the US will cost you 60 lakhs per year minimum. That same engineer in India will cost you eight lakhs.

As a result, companies in India can charge the US companies five times, 40 lakhs and US companies will be more

19:54

than happy to pay because they're still getting a 40% discount. Right?

This was the arbitrage that existed that led to I don't know how many billion dollar industry uh it is today. TCS, Vipro, Accenture, all of this, right?

That led to the development of China and India. In fact, China became a superpower

20:11

because of this cost arbitrage. Yeah.

It's it's a cost arbitrage that led to everything. Now with just it, right?

We are getting into soupy waters. I'll tell you what I mean by that.

Again, I'll go back to the same topic of recession and AI agents, right? Have you heard of tools like cursor, wind surf,

20:27

bolt? No.

These are all AI agents which are specialized to write code. OpenAI's new model 03 is so freaking good with code that it can write code like as if it is the top 200 developer in the world.

So if it goes into a competition

20:44

in the world, it will be in it will be ranked top 200 and it's an AI model. That basically means every company can have thousands of engineers who are the best engineers in the world.

That is 03. That's an AI model.

India makes money by

21:02

writing code and shipping software. If a company in the US instead of relying on India or Indian labor or Indian engineers to build a product, if they can rely on an AI agent which is built on O3 which is one of the best coders in

21:18

the world, would they need India anymore? Okay, you know what?

Maybe they still need India because these AI agents don't operate all by themselves. There is human in the loop.

But with an AI agent, you can write code 10 times faster. I'll tell you one interesting thing.

In the last weekly business

21:35

review with my engineering team, I asked a question. What percentage of code today inside of growth school is written by you guys?

That is you manually write it and it is and what percent is written by AI? The average answer was 65% of the code today is written by AI.

And mind

21:52

you when I say this, the 03 model, which is the holy grail model that I'm talking about, is not available for general public yet. We're using a 2-year old AI model.

That's insane, bro. Right.

Antropics uh which is which is uh which is a company that runs Claude Antropic.

22:09

The founder recently said we are maybe 6 months to one year away from almost all the code to be written by AI. All all the code almost all the code to be written by AI as in we as in claude or the world.

Okay bro I'm telling you 70%

22:27

60 to 70% of the code in my company today is written by AI. Why combinator did a survey where almost in a few companies 90% of their code is already written by AI and the models that all of us are using today is a two-year-old

22:42

model. When a new AI model comes in and this agent is only going to get better at doing stuff, you need a human in the loop.

Best case, if you think about factories, right, most of our factories had the ability to be autonomous already. Aeroplane can fly without a

22:59

pilot. Yeah.

But we still have a human because we believe in human in the loop. That is we somehow believe that if goes down, pardon my French, a human can save which has happened a lot of times and we've got saved a lot of times as well.

The reason why we have humans in a factory even though it's fully autonomous is because we wanted a human

23:16

to turn on the switch, turn off the switch and kind of look at the machine to see that oh everything is going okay. Okay, fine.

That's the job. We are getting to a point where we are believing the system to say I don't need a human in the loop in these technologies.

But the human in the loop element is going to come in code. Right?

23:32

Now one person can write code equivalent of 20 people at a quality of a best engineer. Correct?

Would companies still rely in Indian companies to write code anymore? Would they need it?

That's a big question. Now there's a debate that comes on the other.

The

23:48

answer could still possibly be yes, but then with very less workforce at what cost? H the cost of communication is more expensive than you getting it done.

You know today if you want to build products in fact I'll send you some links you can link them up right I have built full-fledged solutions I don't

24:04

know how to write code in two three hours you tell me a problem today that you're facing while running things cool and if there's a solution and you can imagine that web I wish there was this tool that could do this you can build that in 3 hours today 3 hours 3 to 5 hours max a good strong

24:22

MVP which can do 70% of the things the tools if someone wants to go and explore in your team or anyone are listening to this. There's a tool called as lovable.dev.

So I can do this without knowing anything about coding. No.

You do you know how to communicate? Yeah.

Can you tell what you want? Yeah.

That's

24:37

all it matters. Boss, the future programming language is not Python, is not Rust, is not JavaScript, it's English.

So you should subscribe to communication masterclass guys. It is English and it is communication

24:52

quite frankly because there is this word that you must have that has been thrown around all the places right prompting. Prompting prompting what the hell is prompting?

Prompting. Prompting is all about articulating what you want in the best form so that AI can understand.

What is the language of prompting? English.

Got it. Bro, I've got three

25:09

questions over here and I lay it down in front of you and then you can choose to answer them in whatever sequence. First question.

Now I've understood that because of this trade war regardless of what happens one outcome is recession and even if recession doesn't hit the roof at least companies will look at

25:25

cost cutting. Yes.

This cost cutting will trigger an efficiency exercise and this exercise will lay off a lot of people and it will push the companies to turn existing employees into super efficient employees. Yes.

The

25:41

instrument to do that is AI. Yes.

Got it. Now this instrument of AI for different people are different things.

So if a working professional is watching this episode right now, what are the first three steps that they're supposed to

25:58

take in order to make themselves super efficient? I believe that everybody has to become something called as an AI generalist.

Now what are these AI generalists, right? AI generalists are these people who can

26:14

solve problems using the power of AI. What do companies look for in people?

They are always looking for people who can solve problems. Now with AI journalists, people will companies will look for people who can solve problems with AI.

Why? Because it could

26:29

be 10 times faster, 100 times more efficient. And if there's anybody sitting in a job today and you're realizing that boss, this is going to hit you like nothing else has ever done.

you have to start leveling yourself up as an AI generalist to this right uh I have done this exercise internally with

26:46

my team with with around 20 25 people over the course of last 9 months so there's a road map that I laid out for the team I'll try to lay that out lay that out for you so that people can kind of pick that up there is a level zero to this level zero is where you kind of define your perfect toolkit I'll explain

27:03

you what I mean by that a tool you have 10 things that you do at your work every day and when you Look at those 10 things, right? You would know that these are seven things that AI I can take use of AI right now to do it much faster, much better to I to solve those seven

27:18

problems. There are hundreds of tools out there.

There could be a chat GBD, there could be a Gemini, there could be a claude which are very general purpose tools to very specific tools. Let's say you do a lot of work on Excel.

So there's a tool called as numerous just to understand this better. So the first step is for me to jot down all the tasks

27:35

that I do. Yes.

The second step is to identify merely through human judgment as to which of these tasks could possibly be done by AI. Yes.

Then the third step is to go and find tools to do each of these tasks. Correct.

Correct.

27:51

So when you go out to look for tools, right, the problem is because there's so many tools out there, you will fall into this pit of which tool do I use where there's always a new tool coming in. So the solution to that is to define your AI toolkit.

Okay? Explore a lot of tools.

figure out what works for you and

28:07

hold them very close to you and go very deep into those. But when you say explore these tools, the problem is that the exploration never ends.

And I've been into that uh pit where you know every day there is some of the other Instagrammer who'd come and say this AI tool does XY Z and I'm like bro and I'm

28:24

not saying that they are bad tools. I'm saying that they are great tools but then all of them are great.

For example, for a thumbnail designing tool, we looked at so many tools. We just happened to stick with one.

But then the other day, my editor came to me and said that you know this tool is better. But the only difference between both the

28:41

tools is that I spent more time with this tool and less time with this tool. Similarly, he spent more time with the other tool than he did with my tool.

That is exactly why I'm saying find a tool that you're comfortable with. Go deep.

Okay. So rather than losing your focus and say that oh next big thing, next big thing, next big thing because

28:56

the next big thing is not the next tool. But the problem over here is that GPD3 is not as good as GPD 4.

A problem that let's say I choose a tool which is GP3 level and then tomorrow there's another tool that comes out which is GPD4 level. Mhm.

But they both are on the same tools. Chad GPT you've got 3, four, 4.5.

29:14

So you can understand but with these tools you don't know which models are smarter because A you're not a techie. B with time the tool which is GPT3 level gets better but when you start with a GPT4 level tool it doesn't look that good.

So how do you identify and how do

29:32

you make sure that you always are at the cutting edge of whichever model is the best. I'll get to that.

I will get to that. That's why we're at level zero.

Okay. Level zero is for us to find a toolkit that works right now for us.

Right now. right now right that solves

29:48

an immediate problem that is I'm more efficient at work right away in this for every problem right there are tools for it one great place for you to find tools for your problem is there's a website called as there is an AI for that.com okay okay you go there and search let's

30:04

say excel is your problem you spend a lot of time on excel and you want AI to help you with excel you can just search for excel there'll be 100 tools there look at the one which has highest number of votes okay pick that tool up the other Great place for you to identify if the tool is good or not is to go to product hunt. Search for that tool.

They

30:20

must have launched it. Look at the review of those tools.

What is product hunt? product.com is a platform where founders go to launch their products.

Okay. It's a public forum.

Let's say I built let's say I built a thumbnail designer, right? I will go and launch saying that hey I built a thumbnail designer.

This is

30:36

state-of-the-art. With that being said, there will be other thumbnail designers who have launched there as well and their consumers are also here.

So people who have used other tools like other thumbnail designers would also rate this and they'll be like I saw this tool good but I found this tool to be better than that. So you'll get a highle picture to

30:53

for a starting point on which tool you want to start with. Let's say for Excel there's a tool called as numerous which is a co-pilot for Excel.

Let's say you want to make presentations. A lot of people spend a lot of time designing presentations.

You can use a tool like gamma which can generate out of box for research like we discussed there's chgd

31:10

deep research there's grock research in fact there's a free tool for research which is Google deep research no tool comes closest to that but people don't know about it because really do you think Google deep research is better than chat deep research yeah I'll tell you why I'll tell you the logic of why

31:25

is the backbone of deep research internet what search engine is chat GPD connected to Bing What search engine is Google uh Gemini connected to? Google.

But Gemini is too bad, bro. With the 2.0 model that has

31:42

come in right now, it's phenomenal. Okay, check it out.

Okay. Right.

And a lot of people in deep research, right? You want every corners to be covered.

Well, the quality of output in terms of how it has written the copy, you might

31:57

like chat GPD better purely because of its text generation models and empathy and all those aspects of it. And 4.5 is very good when it comes to emotional intelligence.

Gemini might not be as good. But what do you do research for?

You want depth. Nothing can go as deep as Gemini

32:14

because I have done this activity. same assignment or the same project on Chad GPD deep research on Grock deep search on Gemini uh deep research and on perplexity deep research same thing the most extensive documentation I've got is

32:31

the Google deep research and I'll tell you what chat GPD referred to 40 resources 40 sources Google referred to 350 sources now you might say that web hub we are if doesn't mean that high number of resources would mean high quality of content No, it does. It does.

32:47

In research, it does because it's a intricacies that you have to capture. Correct.

I want to understand an important point that I want you to establish. In fact, anonym is in some cases better than charge or gro which tool is best for what?

33:05

So, there is no tool that is best for anything. I'll tell you why.

Because I I'll tell you this is the response that I was dreading. I I I I'll tell you why and I'll tell you how you can find your right answer.

Also, the foundational problem that people make is with prompt.

33:21

Okay? Your output is as good as your input.

Right? A lot of people screw it there.

Few machines are good with comprehending your question better. As a result, it expands to a better output.

But if you give a high quality prompt to everything, that is when there's a level

33:37

playing field. Okay?

Did you understand? Understood.

With that being said, as a consumer, what do I value more is what matters. For example, when it comes to writing style, Claude was hands down better than everything else.

Was was

33:53

till GPD 4.5 dropped. GPD 4.5 dropped a few weeks back, a month maybe.

And it is purely trained to do good writing. It has emotional uh intelligence.

It has character. It understands what you mean,

34:09

right? better than it understands sarcasm all those aspects human elements come into the picture as a result GBD 4.5 right now is the best writing tool but 4.5 is not free you need a paid version of chity for that so what is the best tool right now cla because you can

34:25

use the free version of it got right same with deep research deep research also goes back into how good a prompt you can write when you write a very detailed prompt on exactly what you want there are two ways of writing a prompt right one is that you say hey do a

34:41

research on US recession and tell me give me a report that is the worst prompt that you can write instead you say I'm I'm making a YouTube video on US recession I want to cover all the sides the impact of US economy or the impact

34:57

that it will have on Indian economy why is that happening is there a bias of AI is there a bias of war that is happening on the other side is there an impact of Trump was there something that Joe Biden did because of which this is happening. You expand your understanding on what

35:12

you want to do, right? And then you put a prompt out.

You're giving it more surface area to think and give you a better output. Got it?

In these cases, I have seen deep research of Google doing better because it goes into those

35:28

trajectories better. It also uses a reasoning model which has a ability to think like a human and reads up and gives you a much more extensive document.

Got it. So for research, Google deep research is better.

For understanding it's free. Okay.

And it's free. So for research Google deep

35:44

research is better. For writing style understanding claude was better but now Chad GPD 4.5 is much better.

And what about Grock? What does Grock specialize in?

Grock's unique edge is that it's built uh by Elon Musk who owns Twitter.

36:00

So no other platform like chat GPT or Antropic or Gemini has access to Twitter data. But how is that a good thing?

Because Twitter is full of crap. But it also is the place where the most recent news kicks in first.

But who is to say that that news is relevant? Perspective,

36:17

bro. Perspective.

But how is that possible? Because bro, I know so many pages which just put out fake news just for living.

No, no. There is community notes that have come in that handles it.

So I'll tell you what I mean by that. Any platform, who who who are these AI assistants catering to?

Humans, right? What is Twitter built on?

36:37

UGC. What do we like to see?

We like and a social network understands what we like to see better than anybody else does. So it understands a human being better than a non-social network platform.

I think that is where Grock does well. It kind of somehow right

36:53

manages to understand your request better and gives you an output that you could relate to. Now is that based on bias?

Possible. No, because my argument is that uh it makes sense if it is about just telling me what people like.

So,

37:09

Twitter is actually trained on all the propaganda, all the crap, all the hate. And when I ask Twitter a question, I'm expecting it to give me a accurate answer which is by definition supposed to not have crap, not have hate, not

37:25

have bias and not have fake stuff, which is everything that Grock is trained on. So that is not how it works basically.

It's not just the information that it's trained with. First of all, Grock is not only trained with Twitter data.

So what

37:41

happens in these large language models is there is unsupervised learning that happens, there's supervised learning that happens and then there is reinforcement learning that happens. I'll explain you what it means by that.

Every model could be slightly different but high level there is uh you basically pull out

37:58

all the content on the internet that you can get hold to books movies everything possible every form of text possible and you just shove that content into the AI model saying read read you don't give context you don't tell what a cat is what a dog is you just say read read and

38:15

understand what you're able to understand that is basically unsupervised learning Next stage once this is done then comes supervised learning where what you do here is you basically say you give some level of labeling some level of direction this is

38:30

good this is not good this is right this is not right but highle labeling you say basically uh it's like giving it books in some form of fashion right again this is called supervised learning where you're directionally telling what it is rather than just throwing data at it then comes reinforcement learning this

38:47

is very important step and this is what makes an LLM an LLM Right here what happens is now the switch flips. Let's say you're an LLM.

I was just giving you data so far. Unstructured data.

Then I give you some structured data, right? In the most

39:02

layman way possible. Then I'll tell you, you studied everything.

Now I'll ask you questions. You give me answers.

In reinforcement learning, what happens is I ask the AI a question, it will give me three answers or four answer, whatever that is. And as a human in the loop,

39:20

there's a human in the loop here with most of the other models. Uh the human kind of rates if which of these are the most accurate answers.

This is reinforcement learning that happens. And on top of all of this, there is something called as parameters that

39:35

kicks in. You basically the model okay these are the characteristics that you should have.

It's like telling a human being be nice, be kind, this is not right, don't do this, this is right, do this. You those are in a way parameters that you give just because you're

39:53

trained. Let's say you just because AI is trained with hundred very negative suicidal books.

AI doesn't become suicidal because reinforcement learning kicks in where you kind of giving it feedback back saying this is right, this is wrong. But in this case with Grock

40:10

while everybody had finite amount of data, Grock I mean Twitter also has finite amount of information but it has more information than everybody else did which is still valuable because more input more quality input leads to a better model. The second aspect to it is

40:26

the reason why it chooses to be haywire and chooses to say whatever it wants to say is because Elon Musk decided to have those parameters set like that. If charge wants to be like very rude which Grock

40:42

is right now right it can be they have to just turn the parameter on saying no filter of being nice being kind being empathetic not not going to talk about elections not going to these are the rules that were set to chat GPT these are the rules that are not set to

40:59

Grock but the quality of output I think you have to give it to the engineers that are working on grock is that at the least amount of time they were able to pull through a model where the quality of output is so good that we're having this debate today. So, long story short, have a toolkit of all the AI

41:16

tools. I'll just summarize this because it's been some time.

Level zero. Level zero, find tasks, find AI for the tasks, research through which AI is the best and then zero down on it.

Done about level one. Now, for you to unlock the next layer of win, you truly have to be

41:33

a problem solver, right? For that, you have to learn a few things.

Level one and level two is where you learn. Now that you use the tools, it's like an app.

You can use it, it's easier, you do all of that. This is where you start going deeper.

In level one and level two, your fundamental job is to

41:50

understand all the AI models out there, not the AI tools. AI models.

AI models out there. Okay.

Right. Like what how does Chad Gypty work?

What is GP 4.5? Just like what we discussed.

Yeah. What is 01?

You're using Chad GP right now. You don't care which model you're using

42:06

at level zero. topic, five right here.

You have to understand where to use a reasoning model, where to use a non-reasoning model, where to use this agent, where to use a open-source model. If there is an open source model,

42:21

how do I run that model? Things like that.

What are the models out there? I mean, essentially here you go deeper, right?

Like, uh, it's a good question. I think the solution to this is being extremely curious.

Instead of letting chat GP go at uh this

42:39

saying that default I'm going to use that you start changing those options playing with it asking it different questions reading about it and that will give you direction there is no other way basically iteration iteration and testing like level one this still gives

42:55

me an understanding of what is the difference between chubity 3 and chity 4 basic understanding answers for example in deep research it takes you um 10 15 minutes to extract the output but once you extract the output that output is just too good okay you can see all those

43:12

sources and quite evidently it is different from the output that charge gibrity 4 would give you right and that input is again different from what charge jubility 3 would give you but you mentioned understanding models what do you mean by that and how can a non- techy person like me do that let's say

43:27

tomorrow you're meeting a hypothetically an investor who wants to invest in things school okay and you want to be prepared for that. How would you use chat GPD for this?

I would first break down why exactly am I having this meeting in the first place? If I'm

43:42

having this meeting just to understand what is the value of my company or let's say no you've decided that you want to raise capital. I want to raise capital.

You want to raise $10 million from this investor. The investor has shown interest.

This is your first conversation not a pitch first conversation with the investor and you have never spoken to an investor before

43:58

in your life. The first thing that I would do is research to understand what exactly do investors find value in by asking Chad What where would you ask Chad 4.5.

Okay. Why 4.5?

44:14

Because I know that it's the best. Okay.

Got it. Huh?

How do they seek value in a particular company? That's step number one.

Then I'll get some parameters. Then I'll go and evaluate whether my company stands by those parameters or not.

Mhm. Once I understand that then I'll feed

44:30

all the data about my company to charge and ask what do you think then it would give me some output and then on the basis of that I would say if you are this investor what are the questions that you would ask me beautiful and then I would prepare for those questions then I would ask Chad ji to be extremely rude

44:47

and ask complex questions which I would possibly not know the answers how would you do all of this who would you talk to in this just chat jubety 4.5 and I've done this for a few of my podcast. I'll not take the name of the guest, but you get what I'm saying, right?

I would just ask JB to ask me all sorts of debatable

45:04

questions, complex questions that I would not understand, and then I would try to answer those questions properly. Eventually, I'll ask for judgment.

Once that is done, then I'll get into the next step. For example, the investor would ask me, "What would you do with these $10 million?" Sure.

The investor

45:20

will try to bog me down by asking for a lesser valuation. Mhm.

the investor will just u ego boost me into believing that uh he's the best and I'm the best and we both should do business. So then I will

45:36

look at all the evil tactics that the investors use. Then I will also look for the red flags in the term sheet.

For example doesn't work like that because

45:51

I'm assuming no assumption assume what if he says no I like it on go on bro 100 crores take it or leave it. Sure you got the term sheet.

What would you do? Then I look for all the red flags in terms will look for it.

I will ask Chad gi how does the term sheet look like? A B I'll

46:07

feed sample term sheets and then I'll ask for red flags and then I'll I'll also ask for all the red flags that a term sheet could possibly have. For example, there's a term sheet make criteria which which says that the investor can decide to sell the stake of the founder.

Yes. After a certain point,

46:24

if the founder doesn't achieve XY Z revenue, the investor has all right to just take up all the stake of the founder by themselves and they also have the right to fire the founder and deploy new management. So I know all of these things.

So I will note down all the red flags. How will you find them in your

46:39

term sheet? Uh I will feed the term sheet to CHBT.

Okay. Now I will tell you a problem that comes.

Your term sheet is 450 pages. We can still feed it to CHP.

No, you can't. Why?

It there is something called as context window. Okay.

Uh and there's a cap of context window. If I'm not wrong, chat GPTs most

46:56

of the models comes with 128k uh tokens. So it will not be able to take more than 40 pages of information.

hypothetically more than 40 pages it will say the file size is too large or the amount of text is too large and if you try to break it down and send

47:12

small small chunks it will forget it will forget there is something called as context window of every all of these large language models right context window is something like memory AI has very short memory right it can only remember so much have you ever realized when you're talking to AI on chat GPT

47:28

sometimes it says the window is getting too long start a new chat why does it say cuz it's going beyond the amount of things it can remember about this window. If you go beyond it, right, it'll stop forgetting the things that you have said in the top.

Basically, chibi is like gajjini. Not gajjini.

It can remember forever but only up to 120k

47:46

tokens. Okay.

Sorry guys, pardon my non-technical language. So, it will not work.

Okay. This is why level one.

Now, I'll tell you if you knew if you have done level one, level two, what you would have done in level one and level two. Like I said, right, you need to know

48:02

which model to use and how models work. If you knew how models work, you would have known that you could not have uploaded just the PDF as is because it would not work.

If it's a 10-page PDF, it will work or else it will not work. If you would have done level one, level two properly, that is you've gone

48:17

through that journey. you would have known you should not have gone to GPT 4.5 but you probably should have gone to 03 high or a 01 pro or one of the reasoning models or a deepseeek R1 or a Gemini deep thinking model why 4.5 the

48:35

reason why you need to know the models is GPT 4.5 is a text generation model that is like I said before this conversation the way these large language models work is that it predicts the next word. So it doesn't have the ability to

48:51

think in a situation of yours which is very very hypothetical. It has to think about multiple use cases on every side.

So it has to do something called as reasoning like a human being chat GP doesn't have the ability

49:07

to think all of this a GBD 4.5 doesn't but a reasoning model does. Oh, when you input the text in a 03 or you must have seen 01 as a model which we never touch saying we don't know what that is

49:22

regular I'm saying purely on regular people right so it does reasoning so the input here should go into reasoning model rather than a regular model right as you talk about it I love the fact what you're doing here is that you said I will ask chat GP to ask me tough

49:38

questions I do the same but I do it slightly differently you could be doing that as Okay, I'm very lazy to type and listen. So I turn on the voice mode.

Correct. I speak for 2 three hours till it breaks and again I resume.

Correct. It's a great way to kind of get a

49:53

balance of what's happening. So there's a reasoning model that goes in thinks through everything, thinks through every equation and goes here and finally you are able to quiz yourself.

You know I've done sample podcasts. I I did a sample podcast yesterday of you and me as well.

Aa is this better? Yeah.

Thank god. Uh

50:09

but Chad Gibb did ask me more tough technical questions which I didn't want you to ask but that's good right uh and then when it comes to if you knew how models work like I said you would know that you cannot just upload a PDF a lot of people actually upload PDF file and

50:25

they say oh it worked it didn't work it just understood what the v what the file is about it doesn't know the intricacies of it when you upload a PDF because it doesn't remember for you to upload a large file you need to know a concept called as I don't want to go into it but rags

50:42

rags break down index so that it can read and chat GP cannot do it out of the box. If your work had had a lot to do with PDFs you would have known of a platform like Humata which is a rack

50:57

platform where you can upload a PDF and start chatting with it or you could have just uploaded the PDF large PDF into a different rag system like notebook LM. Have you heard of notebook LM which is by Google?

I've heard about it but I haven't used it. H Google notebook LM

51:12

you can just upload the PDF. It is also a rack system in a way right the feature that notebook LM is very popular for is the podcast feature where people say you can upload any file AI will convert that into podcast and you can listen to it.

51:27

That is what notebook LM got very viral for. But what it works very well as well for is that you can upload a lot of file aggregate the information inside of it and you can chat about the files that you have just uploaded.

So I can take up Walter Isaxon's book. Yes.

Upload it or

51:43

five different books of Walter Walter Isaxon and ask what are the common trends that you're seeing about the writer? What are the common traits that you've seen in Steve Jobs's Elon Musk?

And it will not the tool the beauty of this tool is that it will not allow it to access information beyond the files

52:00

that you have uploaded. Oh wow.

That is actually very interesting because I tried doing this with the book Prince and I tried to understand if Machi were to give me an advice what would he say? Okay.

And this is what I was speaking about floating with power and trying to understand how power consolidation

52:16

happens. But what happened is that after a certain point it started to go out of the book.

Yes. Now if I haven't read the book I wouldn't understand.

You would not know. Yes.

Yeah. So then that becomes deeply problematic.

Right. But then if there is a model which has restricted access only to the book and it has it has to do reasoning only

52:32

within the book then it makes a lot more sense. Only to the files that you've uploaded.

Got it. So that's a notebook element.

So but then bro there is no end to this. Like you've given me so many nuances.

So give me like a thumb rule on how do I understand these models because this is just too much information for me. There are not 100 models out there.

No you have to understand what are your

52:49

top use cases. Okay.

And then you have there is finite amount of information here. Once you learn that finite amount of information, you will be hooked to make sure that you're always on top of new things that are coming.

Got it. So what's the framework to understand this better?

Uh in terms of which model is

53:06

better for what is I think the only way to do that is by trying is by testing things out is by playing with it. There is no better way of learning than actually doing it.

But playing with it 4.5, you have to be more curious to

53:22

understand what I'm doing. Is it the right thing?

Long story short 3 4.0. Huh?

But that is such an inefficient way to go about it. Why?

Because I've got my day-to-day task. What am I supposed to

53:38

No, you're not going to do this forever. No.

For example, today if I want to have a task, see the first differentiation that I told you about is do you go to a non-reasoning model or do you go to a reasoning model once you know where to go when to go there are bunch of reasoning models everywhere you can

53:53

choose to stick with GP only you don't have to go beyond it but reasoning non-reasoning reasoning or non-reasoning so or else you'd be everybody you want to have an edge you don't want to put in

54:10

the work. No, I'm saying I'm putting in the work, but I have to understand where to put in the work by spending time into understanding where to put in the work.

You getting my point? You know the solution to that?

That is exactly what GPT5 is going to be. It removes like

54:26

this is openly spoken about right now when GPT5 comes right this is not your problem. This is everybody's problem.

They're like we don't know what to use when you have given us 20 models. what do you use where?

So, OpenAI is like you know what the GPD5 is going to be smart

54:42

model which has integration of all the models inside of it. So, you don't have to do the guesswork of which model to use where.

I will understand your task and I will use the right model. So, the call to action is wait for GPI if you want to wait.

But then this kind of

54:57

works in everything that you're learning in AI. Everything that you do in life actually you have to be explorative for you to get an edge.

You need to have more surface area of knowledge. Understood.

Do you think it would be better for example, you ask me this question that uh what if Chad Gibbdy 4

55:13

doesn't take up 450 pages. Do you think a better alternative would be to just ask Chad GPD 4.5 as to what am I supposed to do?

I want to upload 450 pages of document. Tell me which model to use.

Probably but for a question like that, I would go to perplexity. Perplexity.

The reason why I would go to

55:29

perplexity is because GPT 4.5 not tell me that perplexity is better. I think there will be biases there unless you call it out.

I don't know. It's a good try.

These are good experiments. See, this is this is the curious hat on, right?

If it does say, then you're like, "Oh, it's a nice model." If it doesn't

55:45

say, you ask, "Why didn't you answer perplexity?" Then it'll give you a reason why 4.5 Chad Gibb 4.5 explained the yield curve. We were trying to study US recession.

It explained the yield curve

56:00

wrong. Definition of yield curve wrong.

the data the example it gave outdated or it gave the complete opposite example was the e curve recent the the data that you're looking for the no no it was just an example it was a conceptual explanation that I was looking at and

56:16

this is like a 50-y old concept and yet GP 4.5 messed up and we understood that while we were reading through the example and we were trying to understand how can GPD 4.5 be wrong so for about a minute or so we were like stunned that uh GPD 4.5 5 said something and because

56:34

we've trusted the software so many times that we started to question ourselves. There's something called as hallucination.

See all of these models all of this AI right basically has been trained from a lot of information on the internet. So it has a character of a human being but

56:50

it's impossible that it gets wrong information on yield curve because all of the information available on the internet is not 100% accurate. And GBD 4.5 again I go back to the same point.

It is a text generator. It basically guesses the next

57:06

word. If you want super factual information which could not go wrong and it's not creative writing, you would go to something which has access to realtime information which is Google deep reset.

No, you can go to perplex. This is this doesn't need yield curve is

57:21

a basic concept. It doesn't need one.

In fact, a good hack if you want to be very sure of the information that is coming and it's not you didn't ask for it to write an email because the factory cannot be wrong in an email, right? It's about writing style.

But let's say something like this in this case yield

57:38

curve. I would just tap the button of search on on chat GPT.

So before it gives you the answer, it quickly reads up a couple of articles before it gives you the answer. Just this just just takes the quality of the output much higher.

Level one is understanding the models better and here's where you need

57:54

to be very good at problem solving. You said yeah I mean essentially level one idea of level one is that you understand what all models are out there which model is good for what and how to work with them the right way by learning how to do prompting rightly know the right

58:11

models and then choose the right models now let's go to level two level two level two is essentially prompting advanced prompting I would want a framework on how to prompt such that it can give you right outputs and before Before I spoke to An I thought prompting

58:28

is very basic. Okay.

And uh what I found deeply interesting is that me and my team were using the same chat jeopardy model and we had the same problem but somehow the answers that I got were so

58:46

comprehensive that they were like exactly type. Okay.

And I remember this very vividly because two months back I asked the same question to an type like how are you getting such comprehensive answers and he had a different framework

59:01

but I want to understand from you what exactly is your framework because of which you're able to get such comprehensive and complex task done through the operator in just one attempt. Well, it is not just the operator, it's any model out there or

59:16

any AI out there. The way I treat any of the AI agent AI uh assistants out there is how I would how I would treat a intern who has just joined today.

Okay. If I give a task to the intern, I would

59:32

want to be as freaking specific as possible. There are two ways.

Let's say I'm hungry. Okay?

And I have an intern. You should not get your intern to do all of this.

It's just an example. Uh let's say I'm hungry and this intern has joined in today and I'm like, "Hey, I'm hungry.

Can you get me food? The intern

59:49

would be like, "Oh, Weber wants food. Okay, let me go down.

Oh, there's a Burger King right here. I like Burger King.

I'm sure Weber will like it as well, and burger is closer. I'll buy it and give it to you." And he gets me a burger.

I'm like, "Boss, why did you get me a burger?" I go back to the intern

00:05

and say, "Why did you get me a burger?" The intern like, "You said you're hungry. I got you a burger.

What's the problem?" It's like, "Oh, man. I'm dieting right now.

I can't eat a burger." Instead, if I would have told the intern, listen, I'm very hungry right now. I have a lot of work to do.

So, I

00:21

want to eat something which is very quick. With that being said, I'm currently on a diet.

Uh, and I've already had a lot of carbs today. So, I want something which is very, very high on protein and high on fiber.

So, figure out something that we can get really quickly in the next 10,

00:36

15 minutes so I can have this food. Now that I have been a little more and I'm a non-vegetarian, now that I've been a little more specific, the intern will still find a Burger King only, which is closest because I wanted food in the next 15 minutes, but he'll probably order a salad at Burger King with a

00:52

chicken breast rather than a burger for me, which suits my needs. So, it's all about input and output.

So, the more expressive you are to an AI, the better it gets. So, the way I treat it, what do you call this context?

It's not just context. It's a great point.

Context is extremely important. I give more things

01:08

to it. Okay, I call this uh a basic prompt formula.

This is we call it the magic prompt formula fancially inside of group school. And it's a very simple prompt formula.

Okay, I start with something called as role. I go to objective.

I go to context instructions.

01:26

These are the four elements I try to keep in every prompt. And sometimes I add something called as notes.

Notes. And I'll explain you what each one of them is.

All these large language models are general purpose technology models, right? Like they can do a lot of things but that doesn't mean that they can do

01:42

everything really really well. So you have to specify it.

Let's say if I'm writing copy, let's say I'm writing a landing page copy for one of our products. The role is essentially me giving AI a specific role saying listen you are an expert at writing landing

01:58

page copy and you have return landing page copy for top SAS companies like HubSpot, Canva, Freshworks, Zoho etc. and you have 15 plus 15 plus years of experience and you write phenomenal

02:14

conversion copy. This is the role.

Now you'll be like why do I have to give this role? Why are you making stuff up Webhuff?

The answer to this is the moment I give a role to this AI, AI can quickly go up and read what are the traits of a person with 15 plus years of

02:30

experience who writes copy on SAS because it already knows everything but it's clouded. It specifies saying I have to write like this.

A role is very important. Next comes objective.

What do I want it to do? I want you to write a

02:46

kickass landing page for this new AI tool that I'm building that is think school AI right and these are the features of the tool and I want you to build a kickass landing page copy copy for this this is the objective which is the task next comes context now context I feel is

03:03

very very important a few cases you don't need it in a lot of cases you do context is where you tell your AI why you're doing is important okay right so here I say, "Listen, you have a very important job of writing landing page copy. The reason why I want you to

03:20

write great copy is because I'm going to spend $100,000 running ads on this. When $100,000 I spend running ads on this, there's going to be hundreds of thousands of people who land on this landing page.

And if I'm not a if you're not able to convince them about the

03:37

product that we have in the most convincing way, people will not buy my product. when they don't buy our product, we will not do well as a business.

If we don't do well as a business, we would not need you anymore. This is where the context is where you try to explain why what you're doing is

03:53

important. So that positive negative AI works super interestingly, right?

Blackmail this is why what you're doing is very important. You basically control if my marketing will be positive or

04:09

negative. The idea here is to explain why what you're doing is very important.

Why what you're doing is very important. Yeah.

And then there is instructions, right? Instructions is listen, this is my product.

These are features it has. Uh I want the landing page copy to have

04:24

all these captured blah blah blah. These are basic instructions.

Step one, step two, step three, step four. Eventually, there are notes, right?

In notes, you can add anything that you want to summarize or anything that you could not capture here. Right?

And that's my prompt example nodes. So usually the way

04:42

I use nodes is like a backup. I usually don't add nodes.

I write a prompt let's say without nodes and I send this input. Let's say the copy that it comes uh comes in let's say uh second person and I want all of the copy to be in first person.

Now where do I add this? So I

05:00

just add a note and say make sure all the copy is always in first person. Whatever feedback I usually have for the prompt to reuse it over and over the course of time, I usually add it in nodes.

Got it? So L0 is tasks find AI

05:15

tools using those websites. L1 is understanding all the models.

L2 is prompting. Prompting role, objective, context, instruction or notes.

This is one prompting technique. There are hundreds of prompting techniques out there.

Okay. like let's not get into

05:32

that L2 which is prompting prompting and going a little deeper listen what we can do actually interestingly enough is I can give you a document detailed out all the levels which you can link up as well so people can use it okay but it's not as simple as knowing models knowing

05:50

prompting you have to go a little deeper few technical aspects you have to understand but high level you're right models prompting level three may what I feel as an AI journalist because you're problem solver ever just knowing text is not good enough. How do you go deeper

06:05

into audio, video, images and all those things as well? L2 prompting.

Correct. So, so far whatever we have done is with text.

We have stuck with LLMs which are text generation. There's

06:21

a world out there which is massive that has everything to do with images, videos, audio and that is called as a world of diffusion. Okay, that is also something that you need to understand if you want to become a generalist because you are trying to become a problem

06:36

solver and problem doesn't come in just text form. Problem could come in any form.

Okay. So audio and video because video upload video and audio audio I can still

06:51

understand because you can still give instructions via audio which makes it easier. In fact, it is better than text.

Okay. But uh what am I supposed to do with all these because at this point it is almost too much for me to everything will come together on level five

07:07

right trust me first level level zero you did it only for yourself to be feeling comfortable wherever you sit wherever you're sitting at this point of time that is level zero level one you went deeper into all the AI models out there in level two what you did was to

07:24

go deeper into playing and making these AI models You played with prompting, retrieval techniques, what are rags and but yeah level one, level two all of them has to do with LLMs. In level three which is one final curve of learning according to me is

07:40

understanding how do you manage images? How do you generate images?

How do you generate videos? How do you generate audios?

How can you control what is coming out of all of this so that you don't only have the ability of text but you can also solve problems when there's

07:56

a image requirement bro how many of these professional executives have this problem with image because with prompting I can understand you can do code you can write better you can write emails better to emails let's say you have a head of business okay okay okay for your

08:12

operation your business in in your game at least Right? You have a lot of creative work to be done.

If your head of business cannot drive the team under them which is a revenue team to drive them to say that listen your thumbnails

08:28

could be AI first. Lot of re-shoots that you're doing could be a simple audio generated AI of Ganesh.

No, I'm looking at a non-creative company. Tell me one company.

Marlo Infosys. Huh?

Infosys is a service company. They would need this

08:44

even more. Okay.

Because service company has to build solutions for no matter what there is right if you don't have an understanding basic understanding of diffusion it's like LLM is for text diffusion is for image video audio everything else but where will they use it to build products for example let's

09:01

say if a let's say if bank of America comes and says that you guys will have to generate a custom image for every customer who signs into my product okay how will they generate h It's going to be part of our ecosystem. But is that

09:17

going to be as um common as text? For you to become a full stack person, you need to have an understanding of that.

It's as simple as that. Can you not do it?

Probably yes. In the same way, you can choose not to learn how all the models work and stay at level zero also,

09:32

right? For you to have a very good grip.

See I believe as a problem solver the more depth and more width of knowledge you have on things it doesn't have to be that you can execute everything having an understanding of possibilities gives you a new array of solving problems and

09:50

that is what anybody as a journalist should have the capability of got it you must have heard of T-shaped T-shaped leadership T-shaped people right or T-shaped marketers T-shaped business people why do they have to learn about marketing by the way guys just for context T-shaped Mlab specialist in one

10:05

thing and generalist in multiple things. For example, if I'm a specialist in communication and I'm a generalist with video editing, with sound design, with thumbnail design, I can go on to become a YouTube creator.

Anyways, back to the You won't believe the number of founders

10:22

who are running billion dollar companies. You know the kind of founders that I'm talking about.

But I'm sure you are friends with a lot of them have reached out saying webhub how do you generate creatives we see your ads all the time I get the fact that that is AI how the hell do you do

10:39

it these are founders right why do they need to know you are talking about building a generalist you are talking about becoming a builder you're talking about having an edge over everybody else if you don't know it why why are the founders curious to know how we do

10:56

If I was not a AI journalist myself, it's simple, right? If I was not a AI journalist myself, we would not have been the company to launch AI ads one and a half years 2 years back when people didn't even know that you can generate an ad using AI.

What your ads are all AI? 2 years since 2 years we

11:13

have been testing AI. All my ads today is AI obviously.

So you don't shoot them? No, bro.

Rahul bogs me to shoot all these ads so many times. I should just give him my AI.

Not just that, I'm Did you use the general framework of going through h and level abs? And that is one kind of ads that we create.

You

11:29

would also see me in ads where I look like Harry Potter. You would also see me in ads where I look like Iron Man.

You would also see me in ads where I look like a old guy. Aa it is face swapped with me with storytelling.

Interesting. Right now you'll be like

11:44

web this is very marketing specific. Right.

No, I understand because you know Azar from Inshots was here and he said something very interesting. He said that greatness often stems from curiosity.

He said that if you're a curious person then by default you tend to have more information and because you have a lot

12:00

of information you can turn them into bits of wisdom which will take you far far ahead. So he said that in fact when I asked him how do you hire great leaders he said that great leaders have to be inherently curious.

So I think this curiosity aspect is something that I understand and I believe that if anybody wants to climb the ladder of

12:16

greatness, this person has to be curious. If they're not curious and they're just too lazy to explore things.

I mean it's okay to find an it's okay to find a more efficient way to quench their thirst of curiosity but it's not okay to skip curiosity which is why I asked you now there are too many models.

12:32

What is the most efficient way to go about it? I mean I don't want to skip it but what is the most efficient way to go about it?

So I get it. So we don't have to justify curiosity.

It's already it has already been I think it has nothing it has a lot to do with curiosity but it also has to do with one aspect that for

12:47

you to be able to do things at scale you need to have broad broad spectrum of knowledge a general army general probably once he becomes a general is not going to go into the uh war zone to fight with guns anymore unless it gets to it right but are you saying that army

13:04

the senior person army has not tried every freaking weapon that has come into the army. He has and because they're able to empathize with the frontline soldiers, they're able to give them commands that they can obey and efficiently win the war.

So I get it. Great.

So that is done with level three

13:21

levels. Got it.

How would you summarize level three? Level three I can give you some tools or level three is idea of understanding how things beyond text work.

How beyond text work? Because we have done all text so far.

How does video work? How how does AI generate an

13:38

image? What the hell is noise?

Why does it come from noise to a cat photo dancing on a road? Right?

So, long story short, with L3, what you're essentially supposed to do is go beyond text, explore video, audio, and here's where

13:53

11 Labs would come in. Mid I tell you a few tools that people can explore.

Uh Leven Labs is basic, midjourney is basics, Leonard AI is basic. These are tools.

If you want to go a step below this, go into stable diffusion. There is something called as comfy UI which is a

14:09

nice little framework where you can build your own midjourney. Okay.

There are models where you can train your own imagery like flux Laura. If you look at my Instagram thumbnails all of them are me but all are AI generated mean astronaut suit mean this mean that all are AI generated with my face.

Of course

14:25

for video generation there's runway ML uh there is Lumalabs there is Sora there is VO which is by Google which is incredible right? So a lot of these models and this will give you width and depth across everything.

So tomorrow when there's a problem you can solve

14:41

them irrespective of you cannot say oh this is out of my territory because you don't have that option you're done with three levels great you have very good understanding you've played with all of them you know where to use what good job level four and level five is all about building level four where we spoke about

14:58

agents right AI agents are going to enter the workforce level four is where you start learning how to automate things in your life and build agents as a solution for the problems that you have. Build agents.

Okay. Yes.

Right. So, I think the great start for this is

15:15

trying to automate, not do things, but actually hand off your job to something else and get it to do. For example, let's say you're terrible with emails.

And nine out of 10 emails, right? You just want to say not interested.

And you would know there's a logic behind it, right? How can you get

15:31

an AI to automate this for you where it can read the emails, write a reply to the email? If it thinks that there is a with 99% accuracy, Ganesh would send this email as a reply, they would just reply to that email.

If it for some for some

15:46

reason thinks it needs your attention because it is important, it will label it as a different email and keep it with a five different uh replies as a draft. If it is even more important then in real time it will ping you on Slack because you're terrible on your emails.

16:03

All of this happening automatically. Got it?

So L4 is basically exercise executions now. So after you've learned everything, after you have played with everything, now it's time for you to look for that task in your L0.

Which task to pick up, which model to use, and

16:19

how the hell do I automate it so that I go off hands from it? Okay.

Which is the simplest task that you would give out as an exercise for somebody to try out? I think email reply email automation.

Email automation is superb to L0 task.

16:35

Email automation. Uh managing emails, replying to emails.

So I want to process I want you to process it through all these four levels so that we can develop a sample understanding. Sure.

So it's L0 reply emails. L1 understanding the models.

Well, now

16:52

you tell me according to your understanding which is the best model to use in order to reply to these emails. It's a very simple task.

You can use a 40 or a 4.5 or anything. In this case, 40 or 450.

One line key. Why did you choose this model?

4.5. 4.5 because it's

17:08

the best text generation model out there. 40 because it's cheaper than 4.5.

Got it. Then we have L2 which is prompting.

Can you tell me what would your prompt be? You start with role for email reply.

Who usually replies to these emails? Executive assistant right

17:23

of big companies of big founders or whatever. So the role will be like you are a rockstar executive assistant with more than x years of experience and have worked with phenomenal founders like Steve Jobs, Bill Gates, let's say you in this case you can say depender Goyel,

17:39

Kunal Sha or whatever you have been this is a role high level objective your task is to go through my emails open each one of the emails understand what is written on the email and write a reply for it.

17:56

Okay, that is the first job. This is the email reply generator.

Write a reply for that email. Okay, objective.

You have to understand that I am a Ganesh Prasad from Things School. I have a lot of followers.

So, we cannot factually go

18:12

wrong with emails. We cannot be rude to the person.

The email should not a lot of my audience could be sending me love emails. We cannot be like thank you and all of that.

The replies have to be empathetic. whatever other context that you want to give here also we'll get a lot of hate emails you'll get a lot of

18:28

hate emails so manage that with highest uttermost level of respect and empathy as well right we never want to be rude because I am not rude right context instructions in this case instructions doesn't need a lot here you can again

18:45

say that uh basically empathy remember all of these things is a very simple task that's it there is no need of notes because it's a very simple When you write a prompt like this, every time there's an email, it will understand that it's an EA. So, it has to answer like an EA.

It will write nice

19:02

little email reply for every email that you come up with. This is what you did on level zero.

So, when you use this prompt and copy and paste the email that you got, it can write a reply and you have to copy paste it. But this is still copy pasting.

That is level zero. Now, you came to level one and

19:18

level two where you understood how to refine the prompt. So instead of saying write an email reply to this, you wrote a nice little prompt as a result it was able to compose a nice little reply.

Now now you want to do one very important thing that is it has to reply to your email and also put conditional logic. I'll tell you what I mean by that.

On

19:35

level four what you learn is automating this. Let's say we use a tool like make.com or Zapier which has integrations with tools like Gmail and it also integrates with tools like OpenAI where I can use a 40 or a 4.5.

Now I'm not using JB anymore. I've gone

19:50

beyond chat gypty right now. I go to a platform like make.com or a zapia.com for this matter.

There are tools that there are apps that you can pull in. Guys, just to give you context, Zapier is an app which can communicate between different different apps.

For example,

20:07

if you tell Zapio that you should read this email and then go to chat GPT, ask for what would be the best response, extract that response and then paste that over here and then tap reply. Zapier will essentially go from reading

20:24

your email to taking it to chat GPD, extracting the output and then pasting it over here to replying. So it completes the loop of automation from reading to replying.

Okay. So, Zapier is a tool which can actually connect multiple apps together, talk between

20:40

them and get your task executed, which is why it's called an automation tool. If this is clear, let's move ahead.

So, perfect. I think you've explained Zapier really well.

Also, the process that we're going to do here, right? We're going to we're going to pull in Gmail, which is an app inside of Zapier as well.

Once you pull that in, it'll ask

20:56

you, hey, enter your ID and password and sign in into your Google account. You give access to your Google account there, right?

And then you can write a logic every time I get an email on this email id send this email to open AAI or in this case let's say chat GPD for

21:12

easier term inside of open AAI or chat GPD I've already kept the prompt ready so the question comes and it goes into the prompt you write the full prompt and it says here is the email and every time there's a new email that comes out it goes into the prompt executes it you get

21:27

a reply now this reply is again connected to Gmail right And this can all be done without writing a single line of code. All drag and drop.

Right? Then this reply will again be sent on Gmail and it can send the reply.

Got it? Now this is the simplest form.

But

21:43

nobody should do this because it will end up replying every email that you want. So you can put conditional logics that is if this then that kind of logics.

But why not reply to all emails? Maybe you got an investor email.

It doesn't have enough context to it if you force it. A AI is as

21:59

good as it has information of. If you say be nice and let's say investor have written you an email saying hey I want to talk to you.

I want to invest capital and let's say you have no interest of raising money. It'll be like okay great thank you so much for the reply.

I'm super excited to see your reply. I'm so

22:16

glad that you watch our content. Sure.

Let me know when we can talk. And you'll be like I don't want to talk to an investor but AI is just being nice.

And you said be nice. So it went on to be nice.

So it's like a company telling you that Ganesh I want to sue you. Thank you so much.

It was great. Thank you so

22:31

much. It won't be.

It was great. It'll be like I'm sorry to you know uh do something wrong without even knowing if you did it wrong or not.

Uh I didn't mean to do it. We our intentions are always right.

We try to do the right by you and if you have done it sorry we are happy to face the consequences. Oh okay.

22:49

Maybe maybe because you're like be empathetic, be understanding, don't be rude. You said all those things, right?

But here's where you can draw a line. Now imagine you add one more step before even you send that email, right?

Before you can send that email to chat GPT, you

23:05

put a question saying that you write one more prompt. I will send you every email that I get.

Your job is to understand is this a very important email from an investor? Is this an email from a fan?

Is this an

23:22

email from a customer success p for which needs customer success? Is this an email from an internal team member?

Is there an email which is something else? Whatever you can bucket it, right?

You have an understanding of your own email box. If you say then you put a logic if

23:37

it's a customer success executive, if if you understood that this is a learner of things school who has written me an email, positive or negative doesn't matter. Check if it's a positive email or negative email.

If it's an appreciation email, right, send this email to Slack to our team saying, "Good

23:54

job." And also reply to this email saying, "Thank you so much. Thank you for being nice." If it's a negative email, you basically say, "Sorry, didn't expect something like that." And loop in the customer success team by adding this

24:10

email ID to the email and also send this email to customer success or customer issues Slack channel. so that I can get the team can see it right away.

Do we have like a consulting company which can get all this done? I think there's going

24:25

to be a massive rise of AI consultants because I think this is a huge opportunity. There are very very very few people who can do it today and the people who can do it today know are all geeks.

So they're not one of those people who are out there saying that. So that is I was saying there's a massive

24:42

opportunity of people becoming AI consultants transitioning and very soon transitioning from AI consultants to running AI agencies from there I see a possibility of them transitioning into service as a software company or becoming an AI SAS company and actually build something. This is also bought as

24:58

a service, right? Almost.

It's it's this is a classic example of service as a software, not software as a service. Oh, wow.

That is you phrased it so beautifully, bro. Service as a software.

I didn't phrase it. I didn't coin it.

Oh, acha. Okay.

I will not take credit for it. Right.

Service as a software.

25:16

It's a new rise of vocab that's happening. I mean, they can people call it in multiple ways.

AI services company, services software company. Everybody has a different way of saying it.

is essentially those kind of companies where software is replicate is replacing 95% of a human but there is

25:33

still a human in the loop software as a service you have a problem there's a solution you use the solution which is a pure software play and it solves it but service as a software is let's imagine right uh there is company

25:50

Accenture or concentrics which has thousands hundreds of thousands of people employed whose job is to pick up the phone and talk to their customer talk to customers of different companies. 95% of these conversations are predictable to 99% level.

26:17

That is the answer. The cost of that call to the company is 45 rupees.

That is what uh AEL has to pay for a 3minut call. Around 15 rupees a minute is what they have to pay.

These 95% of the things which was being led by human

26:33

beings can be now automated with voice agents. M a company like concentrics will eventually has to become a service as a software company where 95% of these tasks you pick up the phone human will

26:49

not talk AI will talk first but the customer on the other side will not know or will not feel right like hey what is your problem you like I paid but my recharge has not happened like can you wait for 30 minutes did you get the SMS

27:04

said yes was the money deducted Yes. Did you get a SMS from?

Yes. Like you saw in the message, we said your recharge will reflect in 30 minutes.

HDFC has the worst worst bot I have ever seen in

27:21

history. Botan chatbot.

No, there some voice assistant. You press one, press two, press three.

No, bro. It's the worst.

You're talking about press. So I just paid I just bought a

27:38

fan through blinket or I just bought a fan through blinket.

27:54

If this is a if you want to approve this transaction say yes. If you don't want to approve this transaction say no and we will get the card blocked or something.

Yeah. But I said it is a legit transaction but I don't want to go ahead with it because I've made the payment again.

It cannot

28:14

understand. It cannot understand.

Okay. Okay.

No no no no. This is uh block the transaction.

Then I had to go to Bangalore. I had such a terrible 3-day trip because of that.

Bro, it was the worst. And then

28:29

you can't even call them because every time you try to call them because somehow they feel like, oh, you know, they're so advanced that they technology that they're using is not AI. They're looking for a catch word.

No, no, no. What I'm saying is essentially a message to HDFC if you're listening to this that they they may or may not have humans.

I

28:46

don't care about that. But if your AI, if your whatever AI software, whatever you want to call it, if it is so bad, you should at least be able to call a human and tell them that guys, my card is blocked because if it's an emergency, what the hell am I supposed to do?

And

29:01

this is like and it's such a stupid thing that this is the most prestig one of the most prestigious banks in the country. So, it's bad.

Anyways, sorry, bro. No, I get it.

I get the frustration. I think uh like I said, this is an outdated technology right now.

M they use voice in this case but

29:17

they look for a catch word. This was a technology that has nothing to do with the new AI that there is right doesn't have understanding of it.

It's just waiting to listen two words yes or no. Anything else you say it cannot comprehend.

So companies like

29:33

concentric will be able to use AI and they'll be able to dramatically cut the cost and the workforce that they have. Yes.

And so will the companies save, right? because concentric will pass that savings back to the company.

Got it. So I think we've completed the loop now.

Do

29:49

you think this is enough for uh the podcast today? We are at level four.

Oh, we have another level. Yes.

Okay. Take level five.

Level four you end up building automations and AI agents, right? Level five is where you basically whatever problems you have faced so far.

30:06

All right. You can end up building full-fledged solutions to solve your own problem or solve your company's problems.

Okay. Can you give me an example?

Yeah. So again, like going back, let's say you initially as Ganesh, you were doing research for your content.

In level one, what did you learn? You learned that okay, for

30:22

research, I can use deep research. I can do the research and then I will probably use a 4.5 or a claude to write the script.

That is what you learned. But you didn't build any agent so far.

But there's a human that is doing research, copying that content, putting it on

30:38

claude, checking it, adding its own thoughts and then pulling that out and sending that video uh to you so that you can shoot it. How can you automate this whole process in one click?

So you build a platform or you build a tool without writing a single line of code to solve

30:54

your problem. So you build a tool, you basically are replacing the toolkit that you had at level zero by building specialized tools in the end for you.

But when you've got Zapier, why to build a specialized not everywhere you can do it? Not everywhere you can use a Zapier.

31:10

An example in the example that I just told you, you cannot send data across everywhere. You cannot personalize everything everywhere.

You cannot execute things in a few cases everywhere. Not everything will have integrations.

Not for example on Zapier you want human

31:26

in the loop that is you get the research from perplexity's API and you want to add your own thoughts there is no interface on Zapier for you to add your thoughts in the middle there is no human in the loop possible for that it has to be a platform and you build your own platform and you can build your own platform today like I said we spoke

31:42

about cursor we spoke about lovable we spoke about windsurf you just say what you want you just say use this AI model write this prompt for this but this will require a lot of time right three I I built a tool like I told you in 3 hours. But that's because you're you now bro.

31:58

By the end of level five, by the time you get to level five, you'll be an AI journalist. You will be me.

What do you mean? No, I'm getting it because even with prompting, I mean it looks like it's very easy, but once I started to teach people how to prompt, uh, it just gets

32:13

very very complicated. And then you I think it's function of practice.

Ve coding. Have you heard of VIP coding?

No. VIP coding is essentially you building products being a non-developer by just talking to AI.

It's massive right now. What is it called?

Vibe coding. V IB coding.

Got

32:32

it? It's massive right now.

And I'll tell you the world we are heading into. Okay.

You must have heard of personal computers which is laptops. That's the biggest rage that happened at some point of time, right?

Post.com bubble. The biggest rage that will happen right now

32:48

is going to be personal software. You will build your own software.

Build build your own software for you. I legit have a dashboard for with all my data metrics in it with health metrics in it.

I built

33:06

my own software without a single line of single line of I don't know how to write code. I just know what I want.

I iterated, spoke to it because I understand how these models work. I'm able to talk to it in a language that it understands.

It's an pro process of iteration. Your first product will take you five hours, but the second product

33:23

will take you 3 hours. The third product will take you 1 hour because you will know how to talk to it.

That is real learning. Understood?

Now, after having this entire conversation, I still believe that there is a huge scope for AI

33:38

agencies. Like if they just come I think if they can go from level zero to level five and then they can come to companies like think school we will be able to give them all sorts of tasks and then they can execute it by going through this entire blueprint.

The problem is we

33:54

are in a market which is supply constraint there is no constraint of demand. See the the thing is for a large company like a bank of America HDFC they have Accentur Vipros of the world to go to.

Yes, they are slow but they still figure out a solution. Where would a company

34:09

like you or me will go to? I cannot go to Accenture.

I need a specialized solution company which can operate for me and that is the gap but there is no supply. The reason why there is no supply is the reason because 99% of people are sitting on this.

I can't believe they're sitting on

34:26

this. They most of the people think like bro I have done 5 million people.

We have taught 5 million people how to use AI. We still see comments on our ads.

Oh, these guys are going to teach us Chad GPT. Yeah, we can ask Chad GP how to teach it, bro.

Like, just come

34:42

inside. It's you don't even pay.

Just come inside. I'll ask you the same question towards the end.

And we ask this question in each and every one of our sessions. We've done five million people in last I think 18 monthsish, right?

We've asked

34:57

this question every time. Did you think AI was this powerful 2 hours before?

People say no. I had no freaking idea.

True. In fact, bro, I have an idea about it because of Hunch because he keeps updating me about all of these things

35:13

and it they sound very scary. That is the reason why that is the reason why I am actively learning.

Otherwise, I wouldn't be so actively learning about these things and uh after that conversation that I had with you, I started to take my workflows more seriously and I tried to understand how

35:28

to use AI over there. So I mean uh like I said I would still consider myself to be an ignorant fool because I'm aware of all the problems but I'm not acting fast enough because had it not been for an I wouldn't have taken AI so

35:44

seriously. Number two is after having a conversation with you I started to decode all my workflows and I tried to understand where should I use AI to superoptimize them.

You get what I'm saying? Usually you think about optimizing your workflows but now I am thinking about super optimizing my

36:00

workflow. In fact, even while hiring after I had this conversation with Azar, I tried to understand how many of my team members are genuinely curious because what I understood is that if somebody has to be an AI generalist and you coined it very well that AI generalist has to be super curious and

36:18

super aware of all the things that are going on in the market so that they can find AI tools not master them but find AI tools and then master them and then super optimize and super optimize is the Third step. The first step is finding out and that requires curiosity.

And

36:35

there are just so many people I feel so sorry, so sad for them that they are so stupid that they think AI is all about chat gypy or generating text or generating text and to a large extent even I thought the same until a year

36:51

ago. But then uh thankfully I was able to educate myself and after today's conversation I again feel what I felt a year ago which is like an ignorant fool who just doesn't understand how AI operates because it's operating at another level altogether.

So thank you

37:08

so much man. This was information overload and I just hope uh this is information overload in a good way to everybody who's listening.

Guys here's a very simple call to action. Regardless of who you are, if you are an entrepreneur, please go back and evaluate all your workflows.

Like I am

37:24

saying all your workflows. For example, in my company, I am evaluating everything from the Excel sheet that my accountant is making all the way to the edits that are going out.

We're trying to optimize every single process. So, if you're an entrepreneur, please

37:40

re-evaluate everything. If you are a professional working in a company, no matter how boring your company is, no matter how old you think your company is, no matter how orthodox you think your company is, please embrace AI to an

37:55

extent where you can become a super employee because regardless of whether your company stays or not, you will require a job that requires you to be an AI generalist. L0 to L5.

This might sound like great intellectual information, but it is of

38:11

absolutely no use if you don't apply it. So, this is very tedious and by the look of it, it seems tedious to me, but please do it because it's good for you and it's good for your job.

Otherwise, hard times are coming. That's it.

Anything any message

38:26

that you would like to give to the audience? No, I think the way to stay ahead in this race is by uh how do I put it?

Building context, new level of context every day. So by

38:42

keeping up you can only stay ahead today by keeping up. And a lot of like as we speak about it right because a lot of it is new for a lot of people.

They might be like man I'm not a developer. I'm not a software engineer.

I'm not a technical person. How do I do all of this?

38:59

It sounds new. That's why it scares you.

It's not that hard. You just have to play with it.

And once you start playing with it, it is going to be like so exciting for you that you'll wake up every day. Yeah.

Just thinking about what new has

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come I need to explore which is I'll tell you what I wanted to end it with this right. The best thing that is happening today to all of us is AI.

The worst thing that is happening is also

39:30

AI. True.

Right. And we can only leverage this by finding the right balance between these two.

Very exciting times, very scary times as well. But it's on us on how we control this.

Thank you so much, man. This was

39:45

wonderful. And guys, I'm so sorry if I'm acting like a very amateur, nontechnical person because I am.

And uh Weber was a very deeply technical person. So this is a conversation.

I'm not as compared to me, bro. So, I think I've just read more about this than you have.

This is

40:02

basically our phone call but then recorded. Yeah, that is what it sounds like where every 10 minutes I go like what are you saying bro?

What are you saying? And then he says bro um except all the unfiltered words.

So, thank you so much for staying with

40:17

us and I think this was amazing. We thank you so much.

This was wonderful. This felt like a conversation that we would usually have and it was fun, man.

So, thank you so much. Awesome.

Thank you.

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