Apr 28, 2024
72 Hours to $10M: How Deadlines Create Founders
An interview with Inception Studio, Founder of John Whaley
Founder Focused
72 hours. That's how long it takes John Whaley — Stanford professor and founder of three cybersecurity companies — to transform complete beginners into high-value AI startup founders.
Inception Studio is turning conventional wisdom on its head, compressing into just three days what most accelerators do over several months. Run as a nonprofit accelerator that takes no equity, it walks participants through the entire journey in 72 hours: from ideation to recruiting co-founders, forming teams, building a demo, and pitching to investors. One participant used the event to close a $10M seed round led by Andreessen Horowitz.
In this interview, Whaley openly shares how extreme deadlines create startup magic, how to build a real competitive edge amid the AI boom, and the hard-won lessons from two companies that failed.
Watch the full interview now on EO's YouTube channel! Below is the complete transcription of the interview. Minor edits have been made for clarity and readability.
Key Highlights:
"I think the magic of the deadline is that it forces you to focus. Look, I only have this much time. If I have this goal, here's what I need to do to achieve it. And then everything which is not related to that, it just drops away completely."
"We run these 72 hour retreat events where you go from just having a rough idea about what you might wanna do and then meet up with co-founders and then form a team and then you actually go and pitch the company at the end."
"At the end of that event, he had a team, he had a refined idea. He had a demo. He had a pitch deck, and he had a set of investors who were all interested in what he was doing. They ended up raising a $10 million seed round led by Andreessen Horowitz."
"Just because somebody's willing to give you money doesn't mean it's a good idea or it's like worth your time. Your time is worth more than their money."
"If your solution is, hey, we take this amazing thing called GPT-4 and then we just kind of wrap it up in a nicer packaging for somebody else to use, that is not really a great sustainable business."
"We run these 72 hour retreat events where you go from just having a rough idea about what you might wanna do and then meet up with co-founders and then form a team and then you actually go and pitch the company at the end."
"At the end of that event, he had a team, he had a refined idea. He had a demo. He had a pitch deck, and he had a set of investors who were all interested in what he was doing. They ended up raising a $10 million seed round led by Andreessen Horowitz."
"Just because somebody's willing to give you money doesn't mean it's a good idea or it's like worth your time. Your time is worth more than their money."
"If your solution is, hey, we take this amazing thing called GPT-4 and then we just kind of wrap it up in a nicer packaging for somebody else to use, that is not really a great sustainable business."
The 5-Year-Old Who Couldn't Stop Coding
You started coding at an incredibly young age. How did a 5-year-old even get access to programming?
John Whaley: I got started with computers very young, like at 5 years old. My family had bought a computer and we didn't really have many games for the computer. And so my option there was like there used to be these magazines. You would have the listings, like the code listings for games you could type in and then you could run the games. So that's how I got started back when I was 5.
I was in kindergarten and I would just like sit there and type in all the code and then of course as you're typing this you're kind of learning these things and then because I was like not satisfied with just the games as they were, I wanted to be able to make modifications to them and change things about them. And so like I would have to basically learn how to manipulate the code to get it to do what I wanted. So that's basically how I got started.
I was in kindergarten and I would just like sit there and type in all the code and then of course as you're typing this you're kind of learning these things and then because I was like not satisfied with just the games as they were, I wanted to be able to make modifications to them and change things about them. And so like I would have to basically learn how to manipulate the code to get it to do what I wanted. So that's basically how I got started.
Fast forward to high school - you weren't considered a good student, but something changed. What was that turning point?
John Whaley: I've been doing computer science like ever since I was like in high school. I was not a good student. I had all of my teachers and my parents, everybody else, they were like they said, oh, you're gonna go to MIT and you're gonna struggle and you're gonna get C's and like you're gonna fail classes, stuff like that.
My first sense that I was, I'm actually good at this stuff is like there was a qualification round for the USA Computer Olympiad. I'd taken the AP computer science as a sophomore and I did well in the class and everything. And then my teacher there, she learned about the USA Computer Olympiad. She's like, why don't you try this?
And then, so other problems I had in the computer science class were like pretty easy. So the problems they had on the Computer Olympiad, they like these were hard, and there's one problem in particular that was just, it was really challenging, and I was just like, I know there's a solution there. I just gotta figure this out. And then later on I actually found out that I was like the only person in the US that had solved that. One, I think there were 6 problems, and there was like one of the problems that like nobody else had solved except for me, so that was my first indication that would be like maybe I am kind of good at these things.
My first sense that I was, I'm actually good at this stuff is like there was a qualification round for the USA Computer Olympiad. I'd taken the AP computer science as a sophomore and I did well in the class and everything. And then my teacher there, she learned about the USA Computer Olympiad. She's like, why don't you try this?
And then, so other problems I had in the computer science class were like pretty easy. So the problems they had on the Computer Olympiad, they like these were hard, and there's one problem in particular that was just, it was really challenging, and I was just like, I know there's a solution there. I just gotta figure this out. And then later on I actually found out that I was like the only person in the US that had solved that. One, I think there were 6 problems, and there was like one of the problems that like nobody else had solved except for me, so that was my first indication that would be like maybe I am kind of good at these things.
The Deadline Revelation
You mentioned that solving that Computer Olympiad problem was crucial. What did that experience teach you about how you work best?
John Whaley: And then I kind of did the competitive thing again. It was like you have the format there is you have 3 hours and you have to like basically program the solution within a short period of time. In preparation for that, I went to like the local bookstore and this was actually the algorithms book that was used in the MIT class 6.046. And so that was the main reason that I went to MIT because of that book. There's so many amazing algorithms and stuff in there. I love just reading about them and like trying them out. That was kind of like what opened my eyes to like that whole side of computer science.
I was very fortunate to get accepted to MIT because my grades were not great, but I think because I had that computer Olympiad experience, I think based on that, then I got accepted to MIT. I don't think I had any kind of natural like skill and can learn faster than kind of other people. I think I just like was much more dedicated to it because I had that deadline.
I think the magic of the deadline is that it forces you to focus. It's like I'm never able to finish things like unless there's a deadline, but like as soon as like I get that pressure, then it just clarifies everything. It's like, well, look, I only have this much time if I have this goal, here's what I need to do to achieve it and then everything which is like not related to that, it just drops away completely. So I think it's for me personally it's like very clarifying just in terms of just allowing me to like really focus. That's why I was kind of able to achieve the things.
I was very fortunate to get accepted to MIT because my grades were not great, but I think because I had that computer Olympiad experience, I think based on that, then I got accepted to MIT. I don't think I had any kind of natural like skill and can learn faster than kind of other people. I think I just like was much more dedicated to it because I had that deadline.
I think the magic of the deadline is that it forces you to focus. It's like I'm never able to finish things like unless there's a deadline, but like as soon as like I get that pressure, then it just clarifies everything. It's like, well, look, I only have this much time if I have this goal, here's what I need to do to achieve it and then everything which is like not related to that, it just drops away completely. So I think it's for me personally it's like very clarifying just in terms of just allowing me to like really focus. That's why I was kind of able to achieve the things.
The $3 Million Handshake That Changed Everything
After MIT and Stanford, you were planning to be a professor. How did you end up founding your first company instead?
John Whaley: Myself and like some of the other members of my research group in the computer science department at Stanford, we met with Vinod Khosla, who is, you know, founder of Sun, and we talked with him, and then I think it was the next day we received like a term sheet from him. Effectively what he said was like, Here's $3 million go build something cool.
I was actually planning to be a professor. I had interviewed at a bunch of faculty for tenure track, like faculty jobs that I didn't get kind of tenure track offers from either one, so I was at that kind of life stage where it's like I was trying to figure out what to do next and then there's this opportunity. I was like, oh we can found this company. Vinod Khosla is gonna back it and like that was, it's like, yeah, of course I'm gonna do that. So that was my first company, Mocha 5.
I was actually planning to be a professor. I had interviewed at a bunch of faculty for tenure track, like faculty jobs that I didn't get kind of tenure track offers from either one, so I was at that kind of life stage where it's like I was trying to figure out what to do next and then there's this opportunity. I was like, oh we can found this company. Vinod Khosla is gonna back it and like that was, it's like, yeah, of course I'm gonna do that. So that was my first company, Mocha 5.
What was the vision behind Mocha 5, and how did it evolve from your original idea?
John Whaley: Basically at Mocha 5 what we're trying to build was we call the next generation computing utility and like we envisioned a world where you wouldn't have to worry about maintaining software and maintaining your operating system and patching and updates and antivirus and things like that. This is like back in the early 2000s. It's like, oh, I wanted a piece of software. It used to be like you would go to the store and you would like buy a CD and you would install the software on your computer and we envisioned the world where you would be able to call up your service provider and like who's providing your computing service, say hey I want Photoshop, and they would like turn on a switch and then suddenly you would have Photoshop and it could be a new icon in your desktop.
And like we naively believed that internet companies and these kind of like cable companies, your DSL, like they're gonna wanna do this they're gonna get locked in there they're gonna have, they're gonna have all your files. It's providing a great service. And like everyone's gonna want to do this. I was like, no, OK, that's not ignoring the kind of reality of the world.
So the place where you actually started to get traction was when we realized that there's an opportunity on the business side where there's all these companies that wanted to provide computing environments but the people wanted to use their own computers and the big breakthrough for us was the release of MacBook Air. It was like the sexy new computer and like everybody wanted one, but these companies were like, oh well, we're a Windows shop, we're a Microsoft shop.
And like we naively believed that internet companies and these kind of like cable companies, your DSL, like they're gonna wanna do this they're gonna get locked in there they're gonna have, they're gonna have all your files. It's providing a great service. And like everyone's gonna want to do this. I was like, no, OK, that's not ignoring the kind of reality of the world.
So the place where you actually started to get traction was when we realized that there's an opportunity on the business side where there's all these companies that wanted to provide computing environments but the people wanted to use their own computers and the big breakthrough for us was the release of MacBook Air. It was like the sexy new computer and like everybody wanted one, but these companies were like, oh well, we're a Windows shop, we're a Microsoft shop.
You mentioned getting Goldman Sachs as your first big customer. How did that happen and what did it teach you about enterprise sales?
John Whaley: All the business phones were BlackBerry and they had all the features, all the enterprise features, and then iPhone came along and then suddenly people wanted an iPhone and they wanted to bring these into the companies and use them in the company. It was like, well, it doesn't support MDM and all the other things that you need. Well, we don't care, like we wanna use it and so then there's an opportunity there. So we rode that opportunity like the Mac and the Enterprise, the bring your own device, like all of that.
And so that was like when we started to do well is where we kind of really began to focus on that problem. That was the opportunity that existed in the market and then we started to get some early traction there and our first really big customer was Goldman Sachs. We had to do some like crazy sweetheart deal to like get them. It was like not very much money for an unlimited license of all you can eat. They can use us in perpetuity.
That's the type of deal that you have to do when you're an early stage startup because as soon as you got Goldman Sachs, suddenly there's 10 other banks that are all interested because like Goldman Sachs had a great reputation for cybersecurity and like all of that. It's like, oh, if you passed their bar then we're now interested in you, but we made a lot of missteps along the way.
And so that was like when we started to do well is where we kind of really began to focus on that problem. That was the opportunity that existed in the market and then we started to get some early traction there and our first really big customer was Goldman Sachs. We had to do some like crazy sweetheart deal to like get them. It was like not very much money for an unlimited license of all you can eat. They can use us in perpetuity.
That's the type of deal that you have to do when you're an early stage startup because as soon as you got Goldman Sachs, suddenly there's 10 other banks that are all interested because like Goldman Sachs had a great reputation for cybersecurity and like all of that. It's like, oh, if you passed their bar then we're now interested in you, but we made a lot of missteps along the way.
When Success Turns Into Struggle
Despite the early traction, Mocha 5 eventually struggled. What went wrong?
John Whaley: There was a time period where we ended up hiring kind of a CEO that was more of a consumer type and not really enterprise, and we ended up burning a bunch of money through that and like just not really having anything to show for it that kind of later on just ended up kind of compounding over time and so it gets harder and harder as you get to our Series C and Series D. It becomes harder to be successful there and we kind of went through multiple CEOs.
And there's also this is enterprise sales, enterprise deals. It's like elephant hunting. It's either you're gonna like kill the elephant, in which case you've got some big huge like multi-million dollar deal and it's just like hey we blow out our numbers or that PO doesn't come in in time and we also like hiring a bunch of really expensive sales and inside sales people and it's a difficult game especially early on when you are trying to do big enterprise deals as a small company.
And there's also this is enterprise sales, enterprise deals. It's like elephant hunting. It's either you're gonna like kill the elephant, in which case you've got some big huge like multi-million dollar deal and it's just like hey we blow out our numbers or that PO doesn't come in in time and we also like hiring a bunch of really expensive sales and inside sales people and it's a difficult game especially early on when you are trying to do big enterprise deals as a small company.
Looking back at Mocha 5, what were the biggest lessons you learned from that experience?
John Whaley: Some of the big lessons you learned from Mocha 5. Number one, just because somebody's willing to give you money doesn't mean it's a good idea or it's like worth your time. In this case it was like Vinod came and he's like, Oh, I wanna give you money. I was like, oh, Vinod's famous. He's on the Midas list. This must be a great idea. Actually that's not exactly true because your time is worth more than their money.
Another big lesson is like really put a lot of thought and consideration about who you have as investors. Investor may be nice to you, but when they put in a lot of money in the company, there's a lot of expectations there. Push comes to shove, they may not be kind of fully aligned with what the interests of the founders are. So again, being kind of careful about who you have involved in the company.
Your first 20 like your founders and your first 20 employees, they determine like what is the DNA for and the gene pool for your company. Those first 20 employees should be very intentional about who are we hiring, like what are the skills like for the ones that like any of the ones that are gonna stick around there, they're gonna have a huge impact on the future of your company. So like, and what kind of company do you wanna build? Is it like customer focused? Is it like all about product? Is it like technology? Those are all determined by like what is the DNA of the company, and that's determined by the people who are there early.
Another big lesson is like really put a lot of thought and consideration about who you have as investors. Investor may be nice to you, but when they put in a lot of money in the company, there's a lot of expectations there. Push comes to shove, they may not be kind of fully aligned with what the interests of the founders are. So again, being kind of careful about who you have involved in the company.
Your first 20 like your founders and your first 20 employees, they determine like what is the DNA for and the gene pool for your company. Those first 20 employees should be very intentional about who are we hiring, like what are the skills like for the ones that like any of the ones that are gonna stick around there, they're gonna have a huge impact on the future of your company. So like, and what kind of company do you wanna build? Is it like customer focused? Is it like all about product? Is it like technology? Those are all determined by like what is the DNA of the company, and that's determined by the people who are there early.
Finding Authenticity Through Failure
You mentioned going through a difficult period personally during Mocha 5. How did that change you as a founder?
John Whaley: Through my experience going through at Mocha 5, I just kind of fell into that role. I was doing things that was kind of not really like authentic, I guess. I wasn't particularly passionate about that problem, and I was doing a lot of things where it's like, oh, I felt like this is good for my career in retrospect, it was like it put everything in perspective for me about what was actually important in life. The company was kind of like less important at that point, and we ended up at a point where it's like, hey, I was gonna leave the company and then things really just like crumbled from there and they'd have like fire sale in the company and everything.
All that changed when I did UnifiedID. Honestly, I just became much more open and authentic and like honest with people. Curious thing happened when that happened where like people started to react in a much more positive way and then it's like, oh it turns out people like respond to authenticity and like when you're honest about things and they can sense that and then like naturally people like more people wanna follow you. It was like this is a company we wanna build this is the way we want to do things, but it was like very honest and authentic to ourselves and then a lot of things that I'd struggled with in the past became a lot easier just in terms of like things like leadership, fundraising even, or inspiring people and that sort of thing.
All that changed when I did UnifiedID. Honestly, I just became much more open and authentic and like honest with people. Curious thing happened when that happened where like people started to react in a much more positive way and then it's like, oh it turns out people like respond to authenticity and like when you're honest about things and they can sense that and then like naturally people like more people wanna follow you. It was like this is a company we wanna build this is the way we want to do things, but it was like very honest and authentic to ourselves and then a lot of things that I'd struggled with in the past became a lot easier just in terms of like things like leadership, fundraising even, or inspiring people and that sort of thing.
Tell us about UnifiedID - what problem were you trying to solve this time?
John Whaley: I started my second company called UnifiedID. In UnifiedID we solve this problem of identity and authentication. How do you identify yourself in the age of computers, this is often a password. I come up with some secret and I tell you that secret, and then that's how you know that it's me. By the way, I'm not very good at coming up with good secrets because like, I'm gonna reuse them all over the place.
What if we say that we're not gonna require the user to do anything different? They just be themselves. Is there, is it possible to like authenticate them in that context? And the answer actually, yes, because there's a lot that makes us unique. Things like the way that you walk and the way that you hold your phone and the way that you type. You combine them all together, the preponderance of the evidence, and it's like this is almost certainly the right person at that point. So that was the world we envisioned at UnifiedID.
We told a really big story, winning a bunch of pitch competitions because of this. Like we were runner up at TechCrunch Disrupt. We ended up winning at RSA. Based on that, we ended up raising a huge $20 million. It's like, OK, now we have the money. Now let's go in and pursue that goal.
What if we say that we're not gonna require the user to do anything different? They just be themselves. Is there, is it possible to like authenticate them in that context? And the answer actually, yes, because there's a lot that makes us unique. Things like the way that you walk and the way that you hold your phone and the way that you type. You combine them all together, the preponderance of the evidence, and it's like this is almost certainly the right person at that point. So that was the world we envisioned at UnifiedID.
We told a really big story, winning a bunch of pitch competitions because of this. Like we were runner up at TechCrunch Disrupt. We ended up winning at RSA. Based on that, we ended up raising a huge $20 million. It's like, OK, now we have the money. Now let's go in and pursue that goal.
With $20 million raised, what challenges did UnifiedID face in execution?
John Whaley: And then it took us a long time to actually get to the point where it's like the technology reached to the point where it's like we were able to achieve the things that we wanted to achieve. In retrospect, like we would have been better off biting off a much smaller chunk and having that tighter deadline and like that specter of like, hey, we don't have 4 years of runway here, we have like 18 months because it forces a lot of discipline there.
And UnifiedID, we kind of ended up having like too broad of a vision, you know, we didn't achieve our full potential there. There's all these like very interesting intermediate points where we could have spent two months and built something that would have gotten revenue right away and solved customer problems right away.
We eventually got acquired back in 2021, so right before our Series B.
And UnifiedID, we kind of ended up having like too broad of a vision, you know, we didn't achieve our full potential there. There's all these like very interesting intermediate points where we could have spent two months and built something that would have gotten revenue right away and solved customer problems right away.
We eventually got acquired back in 2021, so right before our Series B.
The Birth of Inception Studio
After the acquisition, you found yourself at a crossroads again. How did the idea for Inception Studio come about?
John Whaley: I was kind of at a point in my life where I was like, what do I want to do next? I'm very much a startup person. I like the kind of early stage. I knew that I wanted to do something in like a large language model and generative AI space, you know, I mean AI in general and machine learning, like to do that kind of gait analysis and the other type of stuff we're doing, we're using a lot of sophisticated machine learning algorithms and everything, so from that I was familiar with Transformers and like everything that was happening in the LLM space.
As soon as GPT-3 came out, I knew that there's huge, very interesting commercial opportunities from LLMs. It was began to explore, look around, like try to come up with some ideas. Honestly, I was not making a lot of progress on that because it was me sitting alone in my bedroom just thinking about problems. I had no deadlines. I had no pressure. My life was just too comfortable. Time was just passing by and this was back in 2022. GPT-3 had come out. There's kind of murmurings of like other things GPT-4 that's gonna be coming out soon. I need to make more progress here. This is not good.
I know what I needed. Number one, I needed to get away from everyone and like just remove myself from all my distractions. And so I need to go away somewhere for some short period of time just to be able to like focus. Number two is I needed to be surrounded by other really smart people, most importantly is I needed a deadline.
As soon as GPT-3 came out, I knew that there's huge, very interesting commercial opportunities from LLMs. It was began to explore, look around, like try to come up with some ideas. Honestly, I was not making a lot of progress on that because it was me sitting alone in my bedroom just thinking about problems. I had no deadlines. I had no pressure. My life was just too comfortable. Time was just passing by and this was back in 2022. GPT-3 had come out. There's kind of murmurings of like other things GPT-4 that's gonna be coming out soon. I need to make more progress here. This is not good.
I know what I needed. Number one, I needed to get away from everyone and like just remove myself from all my distractions. And so I need to go away somewhere for some short period of time just to be able to like focus. Number two is I needed to be surrounded by other really smart people, most importantly is I needed a deadline.
So you decided to create your own deadline and pressure environment. How did that first event work?
John Whaley: I go to HackMIT pretty much every year and the TreeHacks and CalHacks. I love the kind of hackathon vibe and scene just like in that kind of intensity that you have and like the fact that just forces you to focus. So like I just sought to kind of recreate that type of feeling and so went on Airbnb, like the vacation rental site, rented out this house in Lodi, which is like middle of nowhere, and I just started calling people up and saying like we have this place in the countryside. Do you wanna like go out there and just brainstorm and hack and just try to build a startup and the topic area was large language models and generative AI.
And so this was in November 2022. The event happened about 10 days before ChatGPT came out, so like the timing was perfect. And then out of that first event actually five companies formed, which is really exciting. And the reason the event was so good is because the quality of the people there was really high.
And so this was in November 2022. The event happened about 10 days before ChatGPT came out, so like the timing was perfect. And then out of that first event actually five companies formed, which is really exciting. And the reason the event was so good is because the quality of the people there was really high.
That success led to formalizing Inception Studio. Why did you choose the nonprofit model?
John Whaley: We wanna run some more of these events, but so we thought about like what kind of structure should this have like, and I've seen things like Y Combinator and TechStars and just a bunch of others like these type of accelerator type of programs. They all had a common failure mode there which was start off pretty good and then they would try to scale and they would scale at the expense of quality and then they would get worse founders the quality dropped and so like there was like an adverse selection problem there where it's like the best people would choose not to go and it starts just like eventual downward spiral in terms of the reputation.
And so it's like well why don't we just do this in a different way? Why don't we make it a nonprofit and we just wanna run these events and put really good people together and when you're a nonprofit, a lot of these questions just kind of melt away about like well who owns the IP? Our goal is not to make a profit off of like these early stage founders that's very shortsighted view.
The genesis of the next billion dollar to $10 billion or $100 billion dollar company is like at that event that is the actual value because guess what, you know, maybe you get a chance to invest early or be an advisor or otherwise develop those relationships. That's where the actual value is. That's where you're gonna get, you know, the 1,000x returns and stuff and that was the genesis of Inception Studio.
And so it's like well why don't we just do this in a different way? Why don't we make it a nonprofit and we just wanna run these events and put really good people together and when you're a nonprofit, a lot of these questions just kind of melt away about like well who owns the IP? Our goal is not to make a profit off of like these early stage founders that's very shortsighted view.
The genesis of the next billion dollar to $10 billion or $100 billion dollar company is like at that event that is the actual value because guess what, you know, maybe you get a chance to invest early or be an advisor or otherwise develop those relationships. That's where the actual value is. That's where you're gonna get, you know, the 1,000x returns and stuff and that was the genesis of Inception Studio.
Navigating the AI Gold Rush
With all the hype around AI, how do you advise founders to build sustainable AI businesses rather than just wrapper companies?
John Whaley: AI space is moving really quickly. The fundamentals don't really change about there's certain fundamentals about building a company. I'm starting a company about like who is the customer, what is the need that like you're actually solving for them? How do you reach that customer? What is your kind of differentiation? How are you 10 times better than what they otherwise have?
If your solution is, hey, we take this amazing thing called GPT-4 and then we just kind of wrap it up in a nicer packaging for somebody else to use, that is not really a great sustainable business there, but if you're solving a real customer problem and you actually have differentiation there, and it could be differentiation in terms of access to data that you have that's really unique, it could be unique insights that you have or it can even be things about like how you bring the thing to market like in terms of I know like all of the people who are in this space and I've sold to them before and they all trust me and so I can bring this to market better than anybody else possibly can that can be your differentiation there.
And like you can still be successful and don't be fooled by the fact that there are businesses that exist that have raised a whole bunch of money. That's all they are fundamentally. Those are not what you wanna be spending your time on. Sometimes people get lucky with the happening businesses for now, but even major ones like with Sora and like these other kind of things that OpenAI is releasing, wow, these are like some well funded companies are now, it's like what happens to Pika Labs once that like Sora is released, it's like, oh, that's a real question there. They're gonna have to keep innovating and end up doing something else because it just becomes really, really hard to compete there.
If your solution is, hey, we take this amazing thing called GPT-4 and then we just kind of wrap it up in a nicer packaging for somebody else to use, that is not really a great sustainable business there, but if you're solving a real customer problem and you actually have differentiation there, and it could be differentiation in terms of access to data that you have that's really unique, it could be unique insights that you have or it can even be things about like how you bring the thing to market like in terms of I know like all of the people who are in this space and I've sold to them before and they all trust me and so I can bring this to market better than anybody else possibly can that can be your differentiation there.
And like you can still be successful and don't be fooled by the fact that there are businesses that exist that have raised a whole bunch of money. That's all they are fundamentally. Those are not what you wanna be spending your time on. Sometimes people get lucky with the happening businesses for now, but even major ones like with Sora and like these other kind of things that OpenAI is releasing, wow, these are like some well funded companies are now, it's like what happens to Pika Labs once that like Sora is released, it's like, oh, that's a real question there. They're gonna have to keep innovating and end up doing something else because it just becomes really, really hard to compete there.
You mentioned there are two games in AI - the big boys' game and something else. Can you elaborate on that?
John Whaley: I think there's two parts to this game and one is like I would call it like the big boys game you're building huge foundational models like the differentiation there is like how many GPUs can I have and what kind of access to data I can have and like that is a game that is very hard to compete with as a startup unless you are very well funded. This is why you need to like raise these billion dollar rounds. It's like Anthropic and Mistral and those ones they're trying to play that game with the Google and the OpenAIs and the Microsoft's and the others. That's a hard game to play because whether you win or not is like determined by your access to data and your access to compute and like how deep your pockets are and you can always like be outspent.
But there's a whole kind of ecosystem that's like that's not that there's great viable businesses there like we can have like a lot of differentiation where you're kind of being AI native like you're actually fully embracing AI in your company and there's a huge massive appetite for this. So if you look at AI budgets maybe 3-4 years ago and like just globally, like IT spend, how much of it is spent on artificial intelligence, I think it doesn't even register on the pie chart. It's like less than 1% now. It's huge. A huge proportion of the money that is being spent is on AI because there's so much promise.
It's really unlocked with ChatGPT and like just like opened people's eyes about what the capabilities of these large language models are and like this in generative AI and agents and everything else, it's not only like there's hype around it, but there's also like real capital behind it as well, and companies are spending like real money, like huge amounts of money to basically develop AI solutions that use AI. So if you can be in that space and you can position yourselves as one of these AI companies, there's massive opportunities there.
But there's a whole kind of ecosystem that's like that's not that there's great viable businesses there like we can have like a lot of differentiation where you're kind of being AI native like you're actually fully embracing AI in your company and there's a huge massive appetite for this. So if you look at AI budgets maybe 3-4 years ago and like just globally, like IT spend, how much of it is spent on artificial intelligence, I think it doesn't even register on the pie chart. It's like less than 1% now. It's huge. A huge proportion of the money that is being spent is on AI because there's so much promise.
It's really unlocked with ChatGPT and like just like opened people's eyes about what the capabilities of these large language models are and like this in generative AI and agents and everything else, it's not only like there's hype around it, but there's also like real capital behind it as well, and companies are spending like real money, like huge amounts of money to basically develop AI solutions that use AI. So if you can be in that space and you can position yourselves as one of these AI companies, there's massive opportunities there.
Finally, we're in a challenging economic environment. How does that affect the opportunities for AI startups?
John Whaley: We're in the midst of this economic downturn. There's layoffs happening and a bunch of other stuff. Economy is not great, like rising interest rates and all. It's a challenging environment if you look back to kind of 2008, 2009, 2010, like so many great companies were formed like during that time. Same thing is gonna happen here.
Some will be like the kind of OpenAIs and like building like these sort of like huge foundational model things. Other ones are gonna be around particular verticals like using generative AI for finance or generative AI for legal or generative AI for marketing. It's gonna end up touching all these different areas and there's gonna be some clear winners there.
Some will be like the kind of OpenAIs and like building like these sort of like huge foundational model things. Other ones are gonna be around particular verticals like using generative AI for finance or generative AI for legal or generative AI for marketing. It's gonna end up touching all these different areas and there's gonna be some clear winners there.
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