Top VC Reveals How to Win the AI Game? | OpenAI’s Billion-Dollar Losses ft. Manav Garg | IBP 48

When Sam Alpin was asked are we in a bubble? He said yes we might be in a

bubble? He said yes we might be in a bubble.

>> How does the AI economics are really working? So I'll give you a simple

working? So I'll give you a simple example.

>> Meet Manav Girk. He is the founder of Together Fund which is the visionary firm fueling India's most explosive AI companies. Today they back massive

companies. Today they back massive outliers in the market including Emergent which is the Indian startup that hit a staggering $15 million in ARR

in just 90 days. And today he's joining us to expose the terrifying speed with which AI evolution is happening. And

he's handing us a survival guide for a world where you either catch the wave or you simply drown. Okay. The next wave of opportunity will come in.

Look at Google the largest company on this planet in terms of search. Highest

market share is trying to think to how will search experience totally collapse, right? So therefore the war has gone to

right? So therefore the war has gone to browsers. I'm able to envision two

browsers. I'm able to envision two businesses talking to each other using agents and that by itself becoming a product.

>> In that case, what has happened is Zumato, Swiggy, Zepu has lost the customer access. So, I think that's

customer access. So, I think that's going to be big fight. I mean, who's going to own the customer?

>> In this subjective world, how do you go there and find a problem that is worth solving using AI?

>> It's a brilliant question actually. If

software is going to become a commodity, how much time will it take somebody else with a similar skill set to create a similar application? That is one

similar application? That is one framework I use. I just want to tell the founders out there don't ignore Indian market. See India is the second largest

market. See India is the second largest market for open AI. Even for GMA 9 million user out 70 million are Indians.

What would you advise a student who's in engineering right now and is 21 years old? If an entrepreneur wants to get

old? If an entrepreneur wants to get funded by together fund, how should they approach you and what should they prepare before they come to you? How do

I not get killed because of a single open AAI update?

Also to the non techies the moment you hear AI you might think this is a very very technical podcast but don't worry about it at all even though this podcast has certain technical terms I will either

explain the terminologies or we will put out trivia so that you are completely aligned all throughout the podcast. Hi

Manav, welcome to the Indian business podcast. Manav, you are one of the most

podcast. Manav, you are one of the most successful SAS founders in the country and now you run a $200 million fund which invests in AI companies. So you

are the perfect person to help us understand what is happening in this wild AI world that we living in. Because

what I find extremely wild about this space is that yesterday while we were speaking you told me that Cursor is about to hit $1 billion in revenue and this is a company that started in 2023.

Lovable hit $100 million in 8 months and your company emergent hit $15 million in ARR in just 90 days.

That is crazy. And while on one side we are seeing these companies pop up out of nowhere on the other side when Sam Alman was asked are we in a bubble? He said

yes we might be in a bubble and because I studied the dotcom bubble what I'm seeing right now is very very similar to what happened during the com bubble and you were there during the com bubble. So

you so you witnessed this time very very closely.

So Marov please help me understand today in this podcast. A what is happening in this AI space right now? B as an entrepreneur how do I find the perfect

gap in the market where I can build a company? see if I have to get funded by

company? see if I have to get funded by together fund how should I approach you and most importantly how do I not get killed because of a single open AI update that is the agenda

for today's podcast shall we get started >> absolutely I'm so excited I'll try to actually share my mental models whatever I know so far >> sounds good so let's start with the first question what is happening in this

AI race how do we have billiond dollar companies popping out of nowhere and what is happening >> if you take whole AI If $100 are getting spent, 70 is going to compute and infra

which is Nvidia and uh and chip infrastructure and cloud hosting providers like Azure, AWS and so forth.

Then $20 are taken by model training companies which is your open AAI and tthropics of the world. Then you remain with $10 which is application layer. So

we are actually now historically of course if you look at Indian economy it is service oriented or SAS oriented where we able to understand how to create an application. Somebody did the research, we're able to multiply that

research, putting engineering might on top of it and create a lot of applications from it. So we playing in this 10 10 cent game so to speak. Right.

>> My question is is there a particular framework that you would like to teach us which will help us find a proper gap in the market.

>> Let me try and give an example. So I'll

take first emergence which is my favorite company right now since I've spent a lot of time with Mukund. Uh

they've done a brilliant job in putting India on the word map I would say. Can

you give us a brief gist of what emergent does so that everybody's familiar?

>> So emergent is a vibe coding platform.

Why coding platform is in the previous word of creating a software like for example if Ganesh has to create a software today what is the process you will go to a services company or you call a friend from engineering college

saying I want to develop an app for my teaching course then he will need a designer to design interface right so you need a combination of team that typically is offered by a services firm and you will end up spending if you're a

European firm or a US firm you end up spending any between $50,000 to $100,000 to create one application then you spend 20% of that on making changes on business is changing then you will find

some domain name you will go to godaddy buy a domain name called thinkchool.com so you will pay some money there then you will host it on Azure AWS or a local data center and you will give some money

to them right that's the typical if you put the entire cost of stack it is 100,000 plus another 20 $20,000 on an annual basis minimum you will spend to

digitize your offering or business now when the AI wave coming in the New whole new era of b coding has come where this entire software creation process is

automated which means you don't need developers anywhere now now if you have an idea let's say think school wants to get an app to automate things school offering you go to a platform like

emergent saying okay I am my persona is student between 15 to 20 year old they're looking for communication classes these are the problems can you build me an app it will then magically

bring an app to you within a span of 15 minutes to 1 hour that's all it takes Wow.

>> Yeah. So suddenly which took us in SAS word one year or a simple app to create 3 months can be done in a matter of few minutes or under an hour. Now that is a timeline. The cost of that is perhaps

timeline. The cost of that is perhaps you will spend $1,000.

>> That's it.

>> That's all. And if you look at the really production ready app maybe you will spend $10,000 as spending $100,000.

So you get a 10x benefit in creating something which you can you never have the access. Number one. Number two it

the access. Number one. Number two it has compressed from idea to creation in that time. I don't have to go to anybody

that time. I don't have to go to anybody and explain because a lot of translation loss of translation happens when I go to somebody to explain. I can now figure out on my own what I'm actually needing.

Right? So that is the whole wave is called VIP coding.

>> You know a few months ago Weber was here web he called growth school >> and when he spoke about VIP coding we made a real of it. A lot of these software developers got angry saying that you know what all of this is

facade. How can you generate an app with

facade. How can you generate an app with just one prompt? So can you please tell them what exactly is the scope of wipe coding so that at least they open their eyes towards the opportunity and not just see it as a threat. There are two things happening in W coding as a

category. So I think the two viewpoints

category. So I think the two viewpoints I'll explain one. So now V coding when we talk production app why it was not solved because when the code number of lines of code increase it gets very complex.

>> Managing that is very hard. So today for example emerging can handle about 300,000 lines of code pretty large code base but when you go into complex apps the technology is not there as of now to

manage the large code bases and then solve the problems within that code base. So this always will be need of

base. So this always will be need of software engineers who can write proper systems, software systems which can then help automate or get AI systems for the organization enterprises. So it is not a

organization enterprises. So it is not a threat to a to an existing developers.

We talk about health a little bit when you are eating food, right? You want to maybe handle your routine in an app.

>> Here you have to pay $100 and the app is ready >> and you can manage your meal. You

understood what you ate. You can show it to your nutritionist. You can show it to your doctor. You can track on your own.

your doctor. You can track on your own.

So I'm able to bring my ideas to life for the first ever time. So what you're saying is that instead of seeing it as a threat that they will take away the existing jobs, what they need to see it

as a market expansion opportunity where people like Ganesh and Mano who otherwise never thought of building an app for their food will use wipe coding to build app for themselves which expands the market.

>> Yeah.

>> And doesn't just shrink it.

>> Yeah. So I think that's actually is the way to have to look at this industry and engineers actually are in more demand right now. If you look at VC data now I

right now. If you look at VC data now I don't know whether you track it or not.

So YC for all these years average age was 30 years for the first time in the last two years average is dropped to 26 year old and 80% of them are engineers actually is is a young engineers and

young minds who are actually building apps faster better shipping at the velocity has never happened before while the shift happens what would you advise

a student who's in engineering right now and is 21 years old what should he do >> okay so I have this famous analogies if you an engineering student at 21 years old, you're already empowered because

you can build something. So if I was 21 year old today or even 19 or 17 year old today, I will actually start building things and put it out there.

>> Like you said the I think the things school story is what resonating me most.

You were very good in communication. You

put some content out there. You say user love it. Okay, now let me put more.

love it. Okay, now let me put more.

Whatever user don't love it, I'll change and put some more. It's the same process for a software developer or engineer.

They are actually more equipped them because they have a software as a leverage, right? I'll get an app or a

leverage, right? I'll get an app or a system, I put it out there. Now the

distribution game is totally changed. I

can go to Twitter, I can go to Instagram, Tik Tok and I can actually use marketing to to get the users to test my product.

>> Yeah.

>> If they love it, they will continue to stick on it and then I know what's working and continue double on it and that's when the companies actually get created. Companies don't get created by

created. Companies don't get created by saying okay let me look at this market opportunity let's do this analysis and then I will do this. See that is very hard to do because you haven't have that life experiences yet. But you able to

understand the creation of the new world. So I would use that superpower

world. So I would use that superpower and look at the problem I'm trying to solve and create a solution for it.

That's the that's the framework I would use.

>> So simple framework is keep looking for real problems and keep fixing them.

>> Yeah.

>> And keep putting your work out so that one fine day you'll eventually end up finding a problem that's large enough that millions of views are willing to pay for it and that will then help you build a company. It's almost very similar to like starting a YouTube

channel. You just find something that

channel. You just find something that doesn't exist. You try your best and

doesn't exist. You try your best and hope that the algorithm picks it up.

>> See, most people drop them because they're not consistent about it.

>> If you go back into the stories, you look at Facebook, right? How did Mark Zuckerberg, he put out something, okay, people have to know each other on the campus. Let me put this and it suddenly

campus. Let me put this and it suddenly took off, right? Actually, most of the stories have been found organically actually >> it is not they thought about a large market that you can do when you have 10 15 years experience behind you. You

understand the domain, you can that's another way of creating the company. But

most of the companies are also a lot of companies get credit organically as well.

>> Now I'm interested in the application space because I can understand that as a non-technical person very well. So I

would like to go deeper into it.

I'll throw a problem statement at you and you tell me if this is something worth solving or not.

Let's take Ditto. Ditto is my favorite company that

Ditto. Ditto is my favorite company that sells insurance. They're the most

sells insurance. They're the most ethical company in the country right now. And if you call them up and you

now. And if you call them up and you tell them that I'm going to buy an insurance that you should not be buying, even if they make more commissions, they will tell you, man, this is not the right insurance plan for you. You should

buy ABC insurance instead.

I think all of this could be automated.

And you tell me if my hypothesis is right or wrong for ditto. Right now, I have to schedule a call then hope that uh I'm free enough to attend that call.

Then I'll attend that call. I'll see all the explanation. Then I'll choose an

the explanation. Then I'll choose an insurance plan for me according to my affordability.

The representative will talk to me about my life and understand my requirements and see what kind of plan do I require and eventually after that is done I'll be sent a link. I have to make the

payment and then I buy the insurance.

In my head it seems as though all of these things can be done by air very very easily. I don't need to schedule a

very easily. I don't need to schedule a call. If I simply talk to a bot

call. If I simply talk to a bot which speaks as well as a 11laps bot it'll be good enough for me to tell them everything the data can be used that data can be matched with a particular

instance plan that will be worthy for me I can be given three options and just like you've got zomato support where you're always given three or four options to choose from to be able to solve your query just like that if I

solve if I pick one such insurance plan and then the payment link is sent to me I make the payment and buy the insurance. The entire process can be

insurance. The entire process can be done in about 35 to 40 minutes. Then if

I have to claim again, if I opt in for a similar process that helps me claim the insurance, then everything that DTO does can be automated. Now to me, this looks

like a hard problem to solve. Do you

think this is a worthy problem to solve and build an application software on top of it?

>> Yeah. So now question is the way you explained is a workflow, right? What do

you explain to me workflow that I first call DTO they send me some plans I look at it I choose one they explain to me then I choose next then send me a payment link I pay and when the claim

comes I go to a particular site tell them customer support agent help me so five steps of so what I call is a workflow automation now in this inherent example if I may be very direct we have

assumed that I will simply automate my existing workflow process that I don't think is a at least my my mental model of thinking about AI I think about how will the future

insurance look like and draw to where I am today. So if I'm creating a system

am today. So if I'm creating a system today, I will not think about what is happening today at all. Actually, I will think about 3 years down the line when AI is even more developed, when I have

more tools, it has memory, it has voice, it has more research, model has 10 more versions out there, it's more much more intelligent than it's today or two years down the line. What will that AI insurance look like? Use the word bot.

It assumption that I will build on a bot. Maybe I don't need a bot. Maybe by

bot. Maybe I don't need a bot. Maybe by

that time now let's do this a little bit more thinking two year hence memory will really handle properly they'll be able to remember every single habit I have maybe the system has already learned in

2 years I'm talking about 2027 let's say we are in December 27 today before New Year's by that time AI will know a lot about Manov they will know he is a founder of together fund founder of a

before he's from small town Punjab his preferences are like that this is my financial model and this is the kind of insurance I need so by by That time AI whatever that form is already knows

Manov's profile financial profile risk profile really really well >> right by that time insurance company system would have also updated so now maybe agent talk to insurance agent and figure everything out it does workflow

is not even required there's no workflow required it only pings five insurance agents one agent from ditto one from New India insurance one from Tata AIG and agents talk to each other and figure out

okay this is the best plan and by that time the agent also able to negotiate Today agents cannot negotiate. There's

no human involved in this. So far agents negotiate with each other. And by that time there's also payment infrastructure for agent. See today there's no

for agent. See today there's no authentication framework for agent infra. So there's a huge payment infra

infra. So there's a huge payment infra has to be created for agentic commerce or agentic payments. There also is line by stripe or you know PTM or all the Google pay have enabled that or UPI has

enabled that. So it's already also able

enabled that. So it's already also able to take my authentication authenticate system pay and come back. Nothing else.

I don't have to do anything.

>> Understood. So let me reimagine this now. Okay, let's say I'm wearing a VOP

now. Okay, let's say I'm wearing a VOP and I use an iPhone.

>> I also wear an >> Okay, so VOP is tracking how much I sleep. Whoop is tracking the strain. My

sleep. Whoop is tracking the strain. My

Apple Health knows how much I walk. My

LinkedIn profile knows my location which is Mumbai, a polluted city. If you

living in Delhi then though you will be sold the best insurance plan in the world because of pollution. So now all my devices can tell the AI about my location because I'm a founder. So it'll

assume that there's a lot of strain. It

will go and verify that through whoop understand that yes this guy sleeps less the strain is very high and also on the basis of blinket they'll also be able to see if I smoke because if I buy cigarettes then I'll search for

cigarettes on blinket. So with all this data because of AI infra all this data can be retrieved and can be sent to an insurance company and that insurance

company will then have an agent which will then say these are three plans that manav must subscribe to and all you have to do is just choose a bc that's it you don't have to choose you may have your agent of your own by that time you may

have a a agent which is learning about you every single time like when you're talking to me your agent is learning about that's how Ganesh talks that's what Ganesh needs a you can tell your agent agent X what is the favorite

character name you could give say whatever name is okay go Jarvis go and find me the best plan it'll go and find and tell you this is the best plan for you basis this is this this is this I have this data I analyzed this it can give you the entire analysis of how they

arrived at this best plan and this is what I need to pay and you just authenticate to your voice okay go and pay head 10,000 rupees a month and I'm a I'm a user of this plan >> got it

>> so if you were to build so if you were to build an AI company in this space to solve this particular problem What would you be?

>> Yeah. So now therefore I'm working actually we're launching initiative next week. This entire is called agentic

week. This entire is called agentic commerce. Not agentic shopping but

commerce. Not agentic shopping but agentic commerce.

>> Agentic commerce. Yeah. Okay. Can you

explain?

>> So today basically your commerce experience is search browse and then purchase. Search and browse take 95% of

purchase. Search and browse take 95% of time. 5% is then check out and finally

time. 5% is then check out and finally everything else right. Uh so that search browse experience will move to agent tech. Basically that's what we just

tech. Basically that's what we just talked about in insurance also. Your

entire experience is basically search and browse. That entire experience will

and browse. That entire experience will get collapsed into agentic form of of in nutshell. I'm just at a conceptual

nutshell. I'm just at a conceptual level.

>> I love how you put it. You said search, browse, purchase. Right now, purchase is

browse, purchase. Right now, purchase is the only thing that is very efficient.

>> But searching and browsing is where most of the industry, in fact, I can think of billiond dollar companies that exist only on the basis of search and browsing. Policy bazar,

browsing. Policy bazar, >> right? All they do is help you search

>> right? All they do is help you search and browse. But you're saying that

and browse. But you're saying that search and browsing can be automated to an extent where you don't have to spend time at all on searching and browsing.

Then my question is how do you envision policy bizarre to evolve?

>> See today a lot of people search and browse because you have time at hand.

You love looking at fashion. Look at

fashion is one category which is totally built on search and browse. Correct. I

love seeing beautiful clothes everything else I can imagine how will I look like.

Right? So then you'll have more time. So

therefore entertainment industry will bloom. So the the opposite effect of

bloom. So the the opposite effect of that is when you have more time at your hand, you have more time to entertain yourself. So entertainment industry the

yourself. So entertainment industry the media entertainment also bloom people listen to your podcast more people that's what I was yeah so that's that's the impact you look at at a macro level and when I'm designing a product now I

have to design like that if I if I'm designing a new policy bazar I actually talk about all those things I will bring health data I'll bring all the insurance data I'll bring financial profile and automatically start giving you the

entire agentic experience of buying then I'll become a policy bazar myself >> so what you're saying essentially is that policy bazar has to think about its existence to the destruction of its old systems.

Yeah.

>> And replacing its old systems with a new system that doesn't exist at all.

>> Yeah, that exactly is the problem we facing. So if you look at it globally

facing. So if you look at it globally also, Google is the only company which is a full stack company and Meta is kind of big trying to get there.

>> What do you mean by that? Can you

explain that to a nontechnical person?

>> We discussed all four layers. It has a chip layer. It has then what do you call

chip layer. It has then what do you call foundation layer then you have the infra layer application. Google has products

layer application. Google has products in all the categories. So they have everything. So therefore Google is able

everything. So therefore Google is able to reinvent itself. It looks very slow to us but actually it is not slow.

They're doing it systematically. I think

they will have a great chance to win.

>> So Man of now I'm again confused. You

are telling me that a company like Policy Bazar has to rethink its existence because search and browsing will become automated. Now every idea that I can think of possibly involves search and browsing only. Even in fact

in fact even if I think about Zumat right now we order from project right you know a week ago I tried ordering from project through an agent okay

because project store was listed the workflow was pretty simple you have to call project place the order ask to

go and collect it put the address of the office put the address of project he will go and collect it payment has to be made and the delivery can arrive It was pretty simple. That's when it got

me thinking why do I need Zumato? I can

simply say, "Hey Siri, please get me XY Z sandwich from Project Hum." And the sandwich can arrive. So everything that I can possibly think of right now is about searching and browsing because

those are the kind of products that that because those are the kind of products that we use every single day.

>> That's the first wave I would say first wave of companies which is good for internet or or that's a wave we are at.

We're talking about wave from here on.

So search and browse experience definitely is going to collapse.

>> So how do we think about an idea? We

again I don't have any idea.

>> No I'm I'm so let's drill down to that.

Let's take example of delivery. Right.

So the core value proposition of Zmetto and Swiggy is also the infra they control which enables the delivery to come in a predictable time frame to you.

If they say it blinket says or Instacart says it'll be with you in 10 minutes, it is there in 9 to 11 minutes. Right? So

that part that supply chain we have to break down into smaller components and understand who's controlling that supply chain. So that will always remain

chain. So that will always remain valuable because delivery infrastructure will build on some logistic support in the end right now that therefore they'll give you moment I collapse search and

browse experience they'll be fight to who will own the customers today's zumato and swiggy are the brands so the biggest fight which we're going to happen now is basically everyone is

trying to launch their own agents right Amazon launched Rufus Rufus has increased the conversion rate of Amazon in a big way which is a again an agent on top of Amazon so every single company

is trying to build their own agents to give you that experience which will collapse your search and browse experience but now as a user I'm independent I don't want to use five agents of five different companies

correct and that is where the open AI or the word of the the venture that we are launching going to talk about that open is also coming in commerce now within chat window for example they're beginning to do that it's big area of

focus for them where you can shop and order everything else moment think a window like a chat GPD this is what I can think right now so maybe we don't need a chatbot going forward I Say I'm you order manav is coming manav loves

healthy food he loves know he wants a protein in the afternoon go and find me this two things he'll go and find order also for you we don't even know who order but in that c what has happened is zomato swiggy zepto has lost the

customer access right customer is with charging this particular case so I think that's going to fight is going to happen I mean who's going to own the customer >> and customer may independent think okay I'm going to create my own agent >> I don't want this hassle of five

different or 100 different agents to talk every day why don't I have my own agent somebody gives me my own agent who knows me, knows my interest, takes care my interest and that agent then it talks to everybody. So we're going into the

to everybody. So we're going into the world where agent will talk to each other that we going definitely in that era right now.

>> Got it. Understood. But now let's talk about GTM. You know I was reading this

about GTM. You know I was reading this uh newsletter by Jaffan Mikdat. He's a

product lead at OpenAI. I'm taking his course also and he speaks about the same thing finding the right problem making sure that you have enough barrier to entry making sure that you keep on collecting proprietary data because

after certain point in SAS it was very difficult to build the product and it was very easy to distribute the product to people because with usage your profit margins don't go down so unlike SAS in

AI as the customer starts using a product your profit margin will start shrinking because of token usage and he spoke about GTM and I want to

understand your opinion on how can I take the product to the market and I also want to understand if you can help me understand when Jav MDA says that distribution is one of the biggest modes

in AI what does that even mean >> okay so I'll take I'll actually give an example of one of my current favorite companies gamma.ai >> gamma.ai >> yeah so gamma.ai AI is automating the

presentations.

Now the rule number one is once you have a product love you get you want to build the distribution. Now what is the first

the distribution. Now what is the first step to build distribution on any consumer product which a consumer consumer means consumer will consume directly is user influencer marketing.

So now the first mistake which most people make is that they are very narrow in the approach. So first rule of thumb so far the learning is you get bit more broader in approach because you do not

know what is going to work what is not going to work. So you have to go little broader in approach.

>> What does that mean?

>> See for example let's say I want to create an edtech product. So my first instinct would be that I will go to all the edtech influencers and advertise on

their on their channels. Right now maybe the fashion influencer is also a very good influencer because same persona is also going to a fashion influence. Same

persona is going to a student is going to a young genz fashion influencer also.

So I would actually should also go and make them recruit them as my influencer.

So like that you have to go more broad-based and more lateral in your thinking when you think of creative influencer based >> because people get affected from different people right I may have trust in somebody which it's not direct the

the correlation is not always direct in the internet economy >> okay so let's take a finance product if a finance product is being promoted by a fashion creator the likelihood of

conversion over there is very less as compared to a finance creator promoting a finance product right >> yeah so I'm okay so if you take a finance as as an example right somebody like you could also be very effective

though you are in education and you're doing some uh to train students or to learn MBA right it is you're not linked to finance as such but maybe you can create a course on it which can be very helpful for the user right maybe you can

distribute the app through your platform which could be very useful for them so you have to think more broader in that perspective now you Ankar Varuk of course is known influencer India who is known for uh finance right go to him of

course you will definitely go to him but you can also go to 10 other influencers which are adjacent to you. So you have to go a little bit more broad based.

>> Got it. Got it. So you're saying that when you say broad uh don't go so broad that your product is being promoted by irrelevant niches but go broad enough so that you don't restrict yourself to just one niche.

>> Yeah. Think of agencies basically. So

you diagram put adjacent. The v diagram will be what are the adjacent industries to finance industry. Where is all education industry all the teachers will come into play. All the wealth managers will come into play. So you go to

adjacent circles and also capture the adjacencies around it. Sounds good.

>> You're the main industry influencer and you have adjacent influencers.

>> So the first method to distribute a product very quickly is influencer marketing. So guys you can sponsor

marketing. So guys you can sponsor things podcast link is in the description.

>> Okay. Next.

>> So then you have to give it 6 months.

You have to create enough budget which is about 10 to 20k a month right now.

You can't say >> dollars >> dollars. Yeah. 20 10 to $20,000 a month

>> dollars. Yeah. 20 10 to $20,000 a month >> for 6 months. You have to try that out.

You can't simply say I will do 15 days and then my budget is only this much. So

which means you have to have $100,000 to $200,000 budget to make sure that you have give enough time for it to do it.

Number three is don't give them the script. Most of the people give the

script. Most of the people give the script. Okay, I'll give the script to

script. Okay, I'll give the script to Ganesh or Manav and they will just write this and post it on LinkedIn or Twitter or or Instagram, right? That looks like a ad which algorithms are able to figure that out because it repeated multiple

times.

>> It rather be organic. It'd rather be the two creation basically that seems to work better than giving a scripted which works like an ad and ad get then caught by the algorithms in a very different

different way. That's the third learning

different way. That's the third learning in in the influencer marketing.

>> Okay.

>> So now let's in the first 3 to four months time you begin to build your product influencer based marketing you will see start seeing some level of success assuming your product is gaining that love on the market. Second mistake

which people do is they don't invest in the brand much often.

>> What does that mean? I explained to you.

So let's say you got 100,000 user in the first three months of the marketing campaign that you started with influencers. Now the there's a trade-off

influencers. Now the there's a trade-off at that point in time. I have million dollars more with me. Should I put now 800,000 of that in more influencer marketing? Right? I go and recruit

marketing? Right? I go and recruit people in the US. I take my product global and I spend more money in influencer marketing. I go to

influencer marketing. I go to performance marketing. I start serving

performance marketing. I start serving ads on LinkedIn. I start serving ads on YouTube. Right? So performance marketing

YouTube. Right? So performance marketing kicks in. So basically after influencer

kicks in. So basically after influencer marketing typical step is a performance marketing because you know what your early understanding of what is working right and then you can go to performance marketing but before performance

marketing actually comes the brand because brands give you consistency of the message. Brand gives that simplicity

the message. Brand gives that simplicity of message which lands well with with the users at a large scale. So many

people actually skip that process because branding is a is expensive step in between. So branding actually does

in between. So branding actually does help.

>> And what all variables will you include in branding?

>> Your value proposition, communication, your taglines, your color, brand identity, logo like lovable has done a beautiful job with that. Everybody knows

lovable, right? You look at it, lovable is a great brand name. They have a heart, the color is all gradient in nature. So they did a very very good

nature. So they did a very very good job. So they hired an agency in the US

job. So they hired an agency in the US which actually created the entire brand positioning for them. So branding

includes positioning, it includes uh communication, it includes brand logos, uh creating an identity for of what offering that you have basically.

>> So once you that that is landing well then it brings consistency in the message because you will see in the early stages of startup a lot of time the message on the uh on influencer marketing in Instagram or LinkedIn

doesn't resonate with the landing page.

You go to landing page some of the messages start showing up right. So the

consistency of the message get lost if you don't have a brand communication sorted out. So that brings the

sorted out. So that brings the consistency with the user. So the user journey becomes very very seamless right if I told you I'm the best in prototyping which is in case of lovable

I from day from the time I start interacting with you on on social media to the time I'm actually using the product >> it'll remain consistent from from first interaction to your last interaction and it stays consistent

>> for the engagement of the of all the things that's the second so I think investing in that brand is really important and then you start laying performance marketing on top of it that's the second learning that we are kind of seeing

Now the ultimate objective is is what that you want to get more organic growth than inorganic growth because inorganic growth which is a paid growth is very

expensive in nature. So typical metric for that is that by 6 month or 4 to 6 months time frame it should be between the organic growth should be 50% plus.

If it is less than that it's extremely expensive. Your customer acquisition

expensive. Your customer acquisition cost is going to go through the roof.

>> What do you mean by organic growth should be 50% plus?

>> Which means people are loving your product so much they're referring.

They're saying oh Ganesh look at this uh iTunes it is so beautiful I went there listen to the song I paid $1 and I was very happy >> so referral rate must be 50%. customer

that comes through that word of mouth basically it's word of mouth or referral what do you call referral also has a technical meaning right now there are a lot of referral networks that works right now which are paid networks I'm talking about no unpaid basically word

of mouth word of mouth is the right way to look at it where you love the product you're saying I this is love the color of the jacket you're wearing can you tell me which brand it is and you will go and buy the same brand because it just looks so good you feel so good to

you right so that is the word of mouth so that typically should be about 50% and that will also true test for you to really see that my product is being loved by the user.

>> Understood?

>> And once you get to that, this is the last point in that then the third point comes in then you work on product improvement so that every product improvement gives you more conversion

>> and that's how the organic engine starts coming in and since you you're improving all your energy is going in improving product you then get into therefore much more retention.

>> Let me ask you better question. How do I become a world-class product guy?

Typically good products are built on simple insights. So typical good product

simple insights. So typical good product managers are very good observers.

They're able to understand the pain point the core pain point really really well. Just like a doctor when we go to

well. Just like a doctor when we go to doctor we talks doctor I my head is paining my hand is also paining and I can't sleep in the night and I have this problem right but doctor says no maybe you have a virus right all the symptoms

that you put together actually leads to only one problem or doctor say maybe your headache is happening because your throat is you must be having a pain in throat therefore there's a headache right so doctor is able to relate the five symptoms that you tell them to one

single problem so typically good or excellent product managers are able to identify that one single problem which will solve most important pain point that a person or a user has and that's

how a very good company is built. So GMA

is a perfect perfect example of that where they built a $100 million business which is profitable and they've just raised capital at two2 billion plus dollar valuation right now. Uh

unbelievable story of how to build a organically good business in this of era of AI.

>> Beautiful. So GTM after you build a substantial product would be to use influencer marketing. Have a budget of

influencer marketing. Have a budget of $10 to $20,000 per month. Give it six months so that you have enough users on board. Don't give creators a script.

board. Don't give creators a script.

Then invest in brand which is positioning, communication, logo and identity. Once you do that, then you can

identity. Once you do that, then you can also infuse money into performance marketing so that you can get more users. And once you've once you've got a

users. And once you've once you've got a very good understanding of your customer persona, performance marketing will pick up. And while you do all this marketing,

up. And while you do all this marketing, you have to ensure that 50% of your customers are coming because of word of mouth and not because of your marketing budget. And as you keep getting more and

budget. And as you keep getting more and more users, if you can collect feedback from the users and keep improving the product, that is how you can build a proper virtual cycle.

>> Absolutely. So there two example cursor has also done it really beautifully and the founder of GMA has put a big post on it. They just raised big round. So you

it. They just raised big round. So you

should all go and listen to the to the video that he has put out there.

There's the learnings from him some of it from our organic learning from portfolio which they may not have done most beautifully but that's the best way to learn presentation.ai AI is also profitable. They're at $8 million scale

profitable. They're at $8 million scale and uh they're also profitable.

>> Got it.

>> And second, I just want to tell the founders out there, don't ignore Indian found Indian market. That's a new learning for AI era. By the way, see India is the second largest market for open AI. Even for GMA 9 million 9

open AI. Even for GMA 9 million 9 million user out of 30 million 70 million are Indians. So India is also big market. Technically most of the time

big market. Technically most of the time we ignore Indian market and we still straight away go global. Yeah.

>> So that's another big thing. I also want to take some time to explain the economics of how it works. the question

that you asked before the go to market.

>> Yeah.

>> As to how does the AI economics are really working. So I'll give you a

really working. So I'll give you a simple example. Let's say you have 100

simple example. Let's say you have 100 rupees.

>> People talk about negative gross margin to start off.

>> What is that?

>> Negative gross margin which it simply means is that if I spend like you also said think school is building an app for example, right? So today what happens is

example, right? So today what happens is when people say I have a negative gross margin of 10% which means I have $100 I have $100 of revenue coming in or I have

$100 to spend $110 are going into are consumed by LLMs either anthropic or open air or or whatever it is right so they are taking million $110 from there

it includes your infra cloud cost also then you have a customer acquisition cost which we spoke about right that takes another $30 to $40 >> how much does infra take up on an

average man Infra means uh cloud >> the cost of LLMs and cloud >> that's what I'm saying 110 if if 100 100 revenues >> 110 >> yeah so it's negative gross margin

that's what is happening right now so if if you have 100 rupees $100 coming in 110 will get paid to LM and cloud that's the current cost structures of in the starting point of launch first 3 to 6

months of launch then 30 $40 will go on your influencer marketing or or marketing as such and then 10 20% will go on product. So that's how your you start

product. So that's how your you start with a negative gross margin. Therefore

the money required is huge. Now the word view is that the cost of LM is coming down drastically and the gross margin will improve because your cost of LMS are going to come down. So therefore

what is the most inefficient cost is the marketing cost. So therefore the

marketing cost. So therefore the efficient growth is valued the most. Now

if I can acquire the consumers organically we just explained in the previous example my 30 40% cost will collapse to 10%. and I put the same cost into product and engineering which means my product is getting better. That's the

real mantra of understanding AI economics and then when the LM cost goes down which it is going down you will start turning profitable and also as you will improve your product you will also

be able to use the LMS in a proper way.

Today what happens is you throw the entire data set to LM and the cost of consumption goes up token consumption goes up. Now as the engineering and your

goes up. Now as the engineering and your product proess comes into play you understand okay I don't have to send every prompt to the maybe I catch something I already know user is going to ask this 100 times so therefore I

already store it rather than going to LM every single time so therefore your usage of LM also become efficient and the cost of LM will come down so gross margin turns therefore much more positive >> got it this is called caching right

>> yeah caching yeah so therefore the AI economics have to be understood really really well and this AI economics therefore cost of customer acquisition in the first 3 to four months plays a very big role. If you get on to good

start on organic growth, you will really really acquire very very efficient growth.

>> Got it. But now I had a very simple question to ask. You know, Chad GBT open air right now is incurring a $5 billion loss. Okay. Do you think it is

loss. Okay. Do you think it is sustainable? Because although

sustainable? Because although everybody's saying that the cost of LLMs will go down, the losses are not coming down at all. How are the LLM costs going down when the losses are not coming down? So what is I explained at the

down? So what is I explained at the start of the podcast that 70% is going going to actually the infra the GPUs and the infra data centers and all this the cost of energy and everything is going

there. So that is the reason if you look

there. So that is the reason if you look at open AAI is going having this all this data center deals that is happening around the world they're also buying stake into AMD right 10% of whatever percent they bought into AMD. So unless

you reduce the cost of the 70%, your overall cost can only then they have only have then 20% cost is a data cost.

They have contracts with New York times they have contract with dit you hear all these contracts which is an acquisition of data because they have to continue to train the models on that right. So the

70% cost will actually when it people say cost will come down it is the cost of chips and that entire infrastructure will get collapsed. So that's the cost we're talking about even if the model training cost remains at 20%. So

therefore they have to become a full stack that's in I give example of Google in the middle of the podcast that you have to control the entire stack eventually to be able to bring down the cost of eventual offering to the

customer. So that's how therefore that

customer. So that's how therefore that becomes your defensibility now right so LM can continue to improve I can continue to switch I can also give the power to the user to choose which LM they want to use then the power is in

the so emergent has done that for example if you go to emergent today you can say you want to use cloud code which is the default option but I can also use Gemini and all I can also use entropic and I can also use any open source right

suddenly therefore user now decides how much money I want to spend for the what quality output I want think about that also right because Now today we assuming the system should decide. Why should

system decide as a user? I will see the value. Okay, I may not need the best

value. Okay, I may not need the best draft. You know I'm letting to my wife.

draft. You know I'm letting to my wife.

Yes, I be the best. I don't have to spend, you know, $1,000 for that. Maybe

I spend $100 and that itself can make her happy, right? And I can use open source for that. That's another way to think about it where you can also pass on that power to the user's hand to decide which LLM is giving you the best output. But then you become that

output. But then you become that orchestration layer in between and therefore there's a defensibility you have built. Right guys, before we move

have built. Right guys, before we move ahead, let me quickly explain what is an orchestration layer so that even the non techies can understand this in the simplest possible way. You see, today AI models are incredibly smart. But the

problem is they're also chaotic. They

sometimes skip steps. They get confused and they're sometimes also unreliable.

So the orchestration layer fixes this problem. It forces the AI to follow a

problem. It forces the AI to follow a strict system. So it locks the sequence

strict system. So it locks the sequence of tasks. It secures the memory and

of tasks. It secures the memory and manages failure by catching errors and forcing a retry. Think of it like answering a two-part question. What is

the population of the capital of India?

If this question is asked to AI to answer this, you need a step-by-step order to be followed. So in this case, the orchestration layer forces the air to do certain steps. In step number one,

it will identify the capital of India, which is New Delhi. Secondly, it will carry that specific city name to the next step. In the third step, it will

next step. In the third step, it will search for the population of New Delhi and this way the orchestration layer ensures that the right order is followed every single time and you receive the

desired result. One of the last question

desired result. One of the last question that I have for you is if an entrepreneur watching this episode wants to get funded by together fund, how should they approach you and what should

they prepare before they come to you?

>> So far, just to give you context, we have invested in 40 companies. We have

deployed the largest early stage investor in AI today. We have deployed about $110 million so far in all these companies. Uh so we've taken large risks

companies. Uh so we've taken large risks to some founders like emergent we gave $5.5 million check. Some we have given a million dollar check for example metapforms was a smaller check on the other hand right. So we can write check

from $500,000 to 10 million actually at a seed stage. So which means take large risks at a very early stages. Now what

really drives the decision-m right? So

first we are a founder first investor.

So first is the founder himself herself.

We look for purpose-driven founders. See

our tagline or internal thought processes we want to find Olympic champions and the reason for that is both Gish and I when we started this fund we build our careers we have built enough money at least to live our life comfortably right

so we are truly a purpose-driven fund we're saying okay we want to put India on the AI global AI map so how do we build India into AI nation for that we think we need to build Olympic champions much like in sports we didn't have many

at that about 5 years back so we're looking for Olympic champions which means more purpose-driven founders so for example couple when you meet mukun you meet som for composio and and akshhat and many other founders or bridge from surprise they all

purpose-driven founders they have a purpose to build something really valuable purpose to change the industries so they're looking at word changing product right when you mukun mukun who's a founder of emergent he will say I want to own the word maybe I can create a full stack offering I can

create my own foundation model and compete with open air one day right so they all looking at purpose right so we are purpose- driven therefore we look for that that are you purpose- driven or are you in for short-term both are fine but we are resonating more with the

purpose purpose driven founder for looking at word chaining outcomes.

Second which I've spoken a lot about it in this podcast and otherwise as well they have to solve a hard problem and not have a hacky way of doing it. You

can iterate it you can hack and then land on a hard problem which is also fine but eventually we should be able to see that you are solving a hard problem or have the intention to solve a hard problem.

>> Now how do you define this problem as hard? So first of all every founder

hard? So first of all every founder thinks he's solving a hard problem like that because you're solving a problem and to you it's a hard problem therefore you are kind of solving it right so hard problem has a context which I said if

software is going to become a commodity >> how much time will it take somebody else with a similar skill set or even a little bit better skill set to create a similar application that is one framework I use right if I have to create one more thing school it is very

hard because you have distribution now you have 4.77 million viewers or subscriber to your channel even if I create something going to take me few years to get here so you have a three year lead time correct so you think of a

lead time so in case of emergent I'll go back to emergent again or even a composio right so emergent has today 3 million apps on the platform 3 million apps >> wow >> so amount of data they generate from that app they have understanding of what

is working what is not working what feedback systems are working which apps are more popular where where should they optimize the algorithm they're writing right now that a new incumbent will find

it very very hard to do right the third point then is if we really solve that part problem who the how the market will look like in V coding if nontechnical users can use it it's a mass it's a

trillion dollar or multi- trillion dollar industry I don't have to think about the industry right so similarly in msk market is very large market and people could not see that it can be a large market but we could take the call

it will become a large market so either you are in existing market which means you're looking after existing revenue pool or you into a new market which is a habit forming market so in AI the word is divided into two kind of market

either you go after exist existing revenue pools or you create a new revenue pool. So we look at that and

revenue pool. So we look at that and have have a viewpoint on that. You know

we may not be right all the time and market may evolve. It is changing every single day. Uh so these are the three

single day. Uh so these are the three main things that we are looking for in a founder and we ability to take large risk. I think large risk taking actually

risk. I think large risk taking actually will then come into play where we give enough freedom to the founder. We

believe we work for the founder and not other way other way around. We will sit with you. We will brainstorm with you.

with you. We will brainstorm with you.

We'll be there when you need us. So

we'll our role is like a coach basically. So if you take Olympic

basically. So if you take Olympic Olympic gold medalist is the ultimate objective. Our role is to become of a

objective. Our role is to become of a coach which means we are available when you need conditioning. We available when you're down. So we will support you when

you're down. So we will support you when you're down when things are not working which happens a lot in the startups as you know and we'll be a partner to brainstorm when things are going really well. So we available for you 24 by7.

well. So we available for you 24 by7.

It's up to you how to use us. So we work for you instead of you working for us.

That's the kind of mental model we have.

That is one of the sweetest things I've heard from a VC man.

>> So Manav if an entrepreneur has to reach out to you how should they prepare so that when they come to you they are well prepared.

>> I think I actually since the AI world is so new and any young mind can come and have a crack at it. I think I would say let's have a brainstorming session. So

if you to do preparation you can come prepared with thought process on how would you how will you create a world changing outcome? How will things

changing outcome? How will things change? But I would love to do a

change? But I would love to do a whiteboarding session for example with you. Let's say if you were come for

you. Let's say if you were come for funding for your edtech app that you want to create, I would say Ghes come I will come to Bombay or come to Bangalore. Let's do a whiteboarding

Bangalore. Let's do a whiteboarding session what it may look like and is it really exciting for you? Is it really exciting for us? Actually, I would do a lot of discussion brainstorming around that. I actually I don't think you can

that. I actually I don't think you can capture the imagination in a slide deck in the world of AI. Yes, slide deck is one of the ways to communicate. You can

communicate your idea. You can say what you're trying to do. But in a I would love to have a face tof face or or a zoom based interaction where we just brainstorm what we're trying to build.

And how would you choose to have a discussion with me? Because I would reach out to you via email. On what

basis will you choose to spend two hours with me?

>> Yeah. So that is a brilliant question.

We get 2,000 plans, right? And we cannot meet as a team. Maybe we meet 10% of them, which is still pretty high. 200

people we meet annually or sometime more. Uh so if I were to choose, I would

more. Uh so if I were to choose, I would look at what areas really excite me.

See, I am a thesis based founder first thesis based investor. If you look at my particular persona, right? I have

certain view on certain industry like you asked me. Fortunately, I know a little bit what about the industries that you were talking about? I thought

about it. I I myself imagine that if I have to create a company, how would it look like, right? So, I'm excited by a few industries. So, if it comes in that

few industries. So, if it comes in that I will immediately say, okay, fine, let's brainstorm and see what really can >> which of those industries can you name top three?

>> It keeps on changing. So, in in the application space, I love this entire SDLC automation. I don't call it VIP

SDLC automation. I don't call it VIP coding. I think lot will be created in

coding. I think lot will be created in this. Emergent is managing the

this. Emergent is managing the nontechnical users. So, there's a code

nontechnical users. So, there's a code review market. Poolside is creating the

review market. Poolside is creating the entire full stack in that for enterprises. Factory days for

enterprises. Factory days for enterprises and India has a lot of expertise in that. We have know 5 million developers who understand SDLC really well. So I would still continue

really well. So I would still continue to look at this market. I think lot more companies can be created in this market.

So I'm very interested in this massive large market.

>> Okay.

>> I'm very interested in voice as infra. I

think whole interaction will shift to voice or a combination of voice and text as we go into the waves. I am looking at memory in a big way. uh I'm looking at security all forms of security AI safety

sec cyber security I think India has done very little in that right now but it's a massive problem deep fakes as you know right everywhere AI security is a massive problem as we get more adoption safety has to be thought alongside not

as an afterthought or if you designed for safety or security up front so privacy security all that is a great area of interest for me and then I think I would say that as such no industry is

out of bonds this is top of mind right now as we speak today after 3 months when you meet me it'll be because industry wave keep on keep on changing right see other themes which are exciting is all see I I'll give a little

bit more framework for industry you pick any old industry where you have a large incumbent I think you can create a paralle company that's the way to think about it so look at legal tech look at

uh HR tech which we discussed recruiting for example you look at the CRM space salesforce has 26% market share very old software you'll get a very large outcome in that entire ERP space will get

disrupted right ERP is SAP The modern ERP is a ERP is going to look very different from what we had a clunky system. You know 50 to 60% of time of

system. You know 50 to 60% of time of the users today go in input that all will change with natural language and and the text based inputs or or voice based inputs into the system. So boring

industry CF office stack is the major.

So that's the way that's the framework of thinking. So these are the areas

of thinking. So these are the areas which I am doing research right now myself right now. We'll keep on changing every 3 months.

>> Perfect. Sounds good. I just want to finalize that that in India I'm actually very excited about the whole commerce again I repeat that agentic commerce in India and edtech and then healthcare

very big topic I'm looking for AI doctor companies somebody has I will happy to >> AI doctor companies >> yeah see India has this massive rural versus urban divide our we have a

shortage we have 150 you know one doctor per 150 people has global average of 60 to1 ratio and then we have a urban to rural divide so rural people don't get that access to the good advice on

doctors and AI doctor actually can solve it provided we can bring accuracy in that right so I'm actually looking for a company in that same fortech also massive impact right we have so much of rural India right who don't have access

to that quality quality teachers are very small in India right anywhere in the world in fact right and we have then huge literacy issue so how do I multiply it so I think that AI in education can really solve that

>> got it thank you so much manov this was wonderful so let me just summarize this entire conversation that we had and you tell me if there's something that I got wrong so that we can correct it for the audience. The first thing that we spoke

audience. The first thing that we spoke about is while you try to build an AI company, try to find a hard problem to solve and hard problems can be solved by first of all understanding what the

future is going to look like 10 years down the line and then reverse engineer to see what can you do today so that 10 years later also you can stay relevant.

We >> 10 years I think is too long horizon. I

think two to three years 10 years is very difficult to imagine right now.

Then we spoke about how to be a great product person and there we spoke about the fact that your acumen of developing a product

can be determined on the basis of whether you are able to segregate a key pain point from the symptoms because when you talk to customers they will tell you all sorts of symptoms all sorts

of symptoms like my head is failing for example you give the example of Amazon if you speak to any customer about how can I make Amazon better for you they will tell you all sorts of things like you know I wish calla I wish I didn't

have to write that email I wish I got better products and so on and so so forth but nobody would think about building blinket so a great product person will think about blinket

through all the customer inputs which have nothing to do with the idea of blinket because the customer will not tell you what to build his job is to consume what you build for them then we spoke about the economics of AI and

here's where you mentioned that today most AI companies are in negative gross margin because if the product is being served at $100 then $110 is going into

infra $30 to $40 is going into marketing and $10 to $20 is going into product development. So we practically have no

development. So we practically have no margin to play at the moment. Which is

why it is important to build a product that can get customer love so that you can eliminate this 30 to 40 rupees cost which is absolutely inefficient and you can choose to either generate profit or

reinvest that capital into product so that you can build a better product.

That is how you can win in the market.

Then we spoke about the GTM strategy and here's where you mentioned that you need to use influencer marketing which is one of the best ways to grow in today's market where you need to have a budget of $10 to $20,000 per month. You need to

stay patient for 6 months. You should

not give creators a script and you should invest in branding as well which is a function of positioning, communication, logo and identity. On top

of that, if you deploy performance marketing, you will get a lot of users.

But the key thing to note is that as you get more and more users, you should be able to make the product better and better so that you have word of mouth.

And here you mentioned a very important metric that 50% of the customers beyond a certain point should be coming through word of mouth and not through performance marketing or influencer marketing. And one advice that you gave

marketing. And one advice that you gave to all the companies using influencer marketing would be to go broad. Do

consider adjacent categories and don't go too niche. At the same time, don't go so broad that you go to irrelevant categories. And then we spoke about the

categories. And then we spoke about the areas that you're interested in where you mentioned SDLC, voice, memory, security and any boring industry that exists today in a large market which can

be disrupted using new ways of thinking.

>> The only correction there is I think the user can be technical or nontechnical.

It doesn't matter not only for nontechnical.

>> Got it. Then we spoke about the three most important things that are required to build a great AI product. Then you

mentioned a world-class product distribution and capital. Capital today

is available in abundance. together fund

can give you access to capital.

Distribution can be gained through influencer marketing which can then which can also be gained through capital. All you need to do is build

capital. All you need to do is build worldclass product. And here's where you

worldclass product. And here's where you spoke about emergent. Um by the way during the start of the conversation we also spoke about search browse and purchase where we had a long conversation about how search and

browsing entirely will be disrupted in the next two to three years which means large companies like Zumato and policy bizarre have to rethink the way they're existing today because a large chunk of

their business is on the basis of search and browsing. If search and browsing by

and browsing. If search and browsing by itself is getting disrupted which means new players will emerge in the market and new systems will emerge in the market. In that case the infrastructure

market. In that case the infrastructure becomes the mode and not the core user interface. Then we spoke about emergent

interface. Then we spoke about emergent where they built they built a world-class product where if there was an operation which used to cost 50 to $50 to $100,000

on top of that if companies were paying 20% for maintenance emergent was able to bring down the cost from $50 to $100,000 to less than $10,000

and they were able to decrease the turnaround time of the app from let's say 6 months to less than a month which helps >> that's an actually in this It's not month hour >> less than an hour which helps companies

go to the market very very quickly which ends up saving them both time and money and that's where we spoke about VIP coding and here's where you mentioned that it's not about VIP coding being a

threat to the developers it's about market expansion which means more and more developers will get the opportunity to hop onto this opportunity which means they can build companies of their own or they can work for these companies or

they can work in companies that are supporting these companies that I think summarizes all the important learning from our podcast.

>> Absolutely love the conversation.

>> Thank you so much, Marov. This was

wonderful. I learned a lot. Thank you so much, Mar. Thank you so much.

much, Mar. Thank you so much.