EVERY SPOKEN WORD
45 min read · 8,617 words- 0:00 – 0:35
Cold Open
- SGSarah Guo
The anxiety that I see is, if you can generate an enormous amount of code and no one is reading it, you don't know the quality of the code. Nobody deeply understands the code base, and there's more fragility, right? It's like the slop problem, vibe coding slop in my actual production code base. But I think the broader problem that new company could go solve is, like, nobody knows how to manage that issue of human attention to engineering. I think it's like open season around this really, really big problem.
- 0:35 – 4:55
The SaaS-polcalypse discussion
- SGSarah Guo
[upbeat music] Hi, listeners. Welcome back to No Priors. Markets are melting down about the end of software. Today, Elad and I are hanging out and asking: Is SaaS actually dying, or are people just projecting five-person startup behavior onto the Fortune one hundred? We'll talk about what's real, incredible revenue growth, collapsing token costs, and faster turnover offenders, what's just hype, and how to size the opportunity. We also discuss the changing bottlenecks in building a software company and some parallels to the internet and cloud eras. Let's get into it. It's good to hang. The, the market is freaking out around us. So in all that noise, what are you thinking about?
- EGElad Gil
Oh, you mean the SaaS, the SaaS-polcalypse?
- SGSarah Guo
The SaaS-polcalypse, the end of software.
- EGElad Gil
Yeah. [chuckles] Software. Yeah, it's kind of interesting. I feel like there's some meta trends that people are getting right and then a lot of specific companies that people are getting wrong. And so, you know, I think... I guess the basic premise is that SaaS software and proceed software will no longer exist, and everything's gonna be replaced by AI, and everything's just gonna get vibe coded. So why would you pay X dollars for a Salesforce instance when you can just vibe code it internally? And all that stuff strikes me as incredibly short-sighted in the near term. Over the long run, who knows what happens in twenty years or whatever, but there's lots and lots of companies that are quite durable. I think an interesting example of that, where I'm still a shareholder, is Samsara, where, you know, nobody's gonna vibe code a fleet management app that will then get distributed through, like, what? Vibe sales, vibe, you know, enterprise sales or something. [laughing] And you're gonna build a vibe like in-cab camera sensor that everybody will install in these fleets, and then you're gonna support them using vibe agents or something. It's just, it's just very overstated. So I feel like it's one of those things where there's a massive market correction around something that, in the long run, has a lot of truth to it, and maybe in the short run for certain types of companies, has a lot of truth, right? Ultimately, I think Decagon and Sierra are, are examples of companies where you're moving from proceed software to basically utilization-based customer support related agents, right? That is a real shift that may impact some of the prior wave of sort of proceed software companies, but this isn't gonna be every single SaaS company. So I, I, I view it as very short-term overstated. In the long run, who knows? How about you? How do you think about it?
- SGSarah Guo
I mean, I, I think the idea of vibe enterprise sales is hilarious, um, because I... We have portfolio companies with, you know, hundreds of millions of dollars of revenue, who are very committed to as much token usage as we can, as few great people-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... as we can have. And today, you know, they've less than fifty engineers, and they went from-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... zero to, like, let's say, close to a hundred salespeople very quickly-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... right? And so it's just a, a view from the l- growing AI natives that, like, vibe sales is not happening, right? Like, a, a-
- EGElad Gil
Oh, yeah, vibe sales is definitely-
- SGSarah Guo
[chuckles]
- EGElad Gil
... never gonna it's, it's not happening anytime soon.
- SGSarah Guo
Yeah.
- EGElad Gil
And so it's just, again, all this, it just seems like a very strong market reaction and market correction, and it, it seems like it's very overstated, especially relative to a handful of companies that you're just like, why? Like, how will you displace this company with, uh, coding and, y- you know, the fleet example, you're not gonna have the fleet managers, like, writing their own apps to do all this giant surface area of stuff. It just doesn't... It's just not gonna happen in the short run.
- SGSarah Guo
I think a lot of it's actually driven by, um, some assumptions that, you know, persona close to my heart, but engineers and builders are making about, like, the rest of the world, right?
- EGElad Gil
Mm-hmm.
- SGSarah Guo
I- because there's this, there's this implied belief that, like, everyone will want to make their own software, and I think it's like prob-
- EGElad Gil
Mm, software is eating the world. Is that what you're trying to say?
- SGSarah Guo
I, I am not... I, I think-
- EGElad Gil
[chuckles]
- SGSarah Guo
... like we're, we're still-
- EGElad Gil
Time to build, Sarah. Time to build.
- SGSarah Guo
I don't think that everybody wants to make their own software.
- EGElad Gil
[chuckles]
- SGSarah Guo
I think some set of people-
- EGElad Gil
Yeah
- SGSarah Guo
... will wanna make it, and others will want other people to do it for them. And, like, sometimes, like, what's a, what's a, uh-
- EGElad Gil
Mm-hmm
- 4:55 – 5:43
AI Change Management in Large vs. Small Companies
- EGElad Gil
You didn't have to vibe code anything. And so for very limited niche applications, where it's a technical team doing something really quick 'cause it's useful and custom and bespoke, amazing, of course, that's gonna happen. Does that mean that a Fortune one hundred company is gonna displace their CRM with some internal thing they got vibe coded over the weekend? Probably not. And so I think it's also extrapolating or projecting behavior of very small technical startups onto the world's biggest enterprises, and that's the second thing people are getting wrong, is they're misunderstanding the, the moment. And I think the internal software stuff that people are building is amazing, right? It's not... Like, it isn't impressive that you can do that. It's incredibly impressive. It's just extrapolating that behavior so aggressively, so early, just doesn't make that much sense right now.
- SGSarah Guo
I think to your point of, like, the five-person company versus the very
- 5:43 – 8:38
“Is Software Eating the World?”
- SGSarah Guo
large enterprise, if you ask that same engineer who's, like, pissed about paying ten dollars a seat for Jira-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... like, if you asked him or her: like, "Do you wanna do the change management in Bank of America, of getting everybody to do this the way you think is right? And then dealing with all the security considerations and managing other people's opinions about potential changes to the story management workflow and then maintaining the system," the answer is, like, probably not.... you know? Um,
- EGElad Gil
Mm-hmm.
- SGSarah Guo
And so I, I think it's, it is focused on, um... I actually think the idea that actual production of code becomes not the bottleneck for, um, if you know what the spec is, not the bottleneck is, like, incredibly interesting, but I, I, I do think it overstates like how much-
- EGElad Gil
Mm-hmm
- SGSarah Guo
-uh, of the overall software vendor problem that is.
- EGElad Gil
Yeah. I think people also misunderstand how much demand exists for software products, and by software products, I mean everything. I mean AI, I mean-
- SGSarah Guo
Is software eating the world?
- EGElad Gil
You know, different tooling.
- SGSarah Guo
Is AI eating the world?
- EGElad Gil
AI is, AI is eating the world, so I think that, that is actually true, and I think Mark's post on that was really, um, thoughtful and forward-thinking on it all. I think that fundamentally, um, you know, there's, there's so much demand for software, and there's so little supply of engineering in reality relative to that demand, that as you add this enormous boost of productivity to software engineers, um, it just gets sucked up, right? Because there's so much more stuff to build and to do. And I don't see teams, you know, start-up teams continue to hire engineers for a reason, you know. I think the nature of the work is shifting, and I think some people are gonna have real issues with that shift. Because fundamentally, you're shifting from, you know, in some cases, you know, there's the... There's a few different types of, of mindsets around engineers, and one of the mindsets is the really bespoke craftsmanship. You know, "I'm gonna make-- I, I'm gonna do the aesthetics of the thing that I'm doing really well, and I care about the code quality and, you know, and, um, the, the artisanal version of what I'm doing." And then there's people who write code because it's a utility that allows them to build product. There's some people who really like aspects of the math or al-- you know, there's lots of different motivators for people to write code, and I think a subset of those people are gonna be, uh, less happy in the new world. It's kinda like the indie game developers who make these handcrafted individual games for themselves and then for their friends, and then they launch them on the Apple Store or whatever, um, versus the people who'd work at EA.
- SGSarah Guo
Mm-hmm.
- EGElad Gil
And they each have their own version of craftsmanship, but it's just a different type of thing. I think we're gonna see a lot of these really great engineers who care about the, the bespoke craftsmanship of everything they do, they're gonna be unhappy working at larger companies as these coding tools get even more accelerated. Because it goes against their approach of, of how they like working and what they enjoy out of the work. And for other people who are really focused on the utility of just building product, it's gonna
- 8:38 – 14:00
Addressing the Unsolved Problems
- EGElad Gil
be freeing in some ways. So I think there's also, like, a variance in terms of the reactions to this stuff, depending on the type of, uh, utility function that you have relative to the work you're doing.
- SGSarah Guo
Yeah. I, I think related to that, the, um, one thing I've seen is that if you have an engineering identity that's based on the, like, a value-based ranking of difficulty or skill, like the, the specific types of engineering that are considered, you know, impressive or high status can actually be, like, less hard-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... for agents, right? So I think there's an enjoyability d, like, element and then an identity element.
- EGElad Gil
Mm-hmm.
- SGSarah Guo
Um, and actually one of your founders, um, from Applied Intuition, wrote a good blog post where there is a, um, an essay where he says, like: "Keep your identity small." I think that's, like, wonderful overall advice for this-
- EGElad Gil
Mm
- SGSarah Guo
-period of time.
- EGElad Gil
Mm-hmm.
- SGSarah Guo
Right? You're, like, more adaptable if it's true.
- EGElad Gil
Mm-hmm.
- SGSarah Guo
But I, I think your overall view of there are a lot of unsolved problems, and, like, making an abundance of software can better address that-
- EGElad Gil
Mm
- SGSarah Guo
... I, I strongly agree with. And one, one thing that, um, actually is near and dear to the audience that is really unsolved is, like, we've broadly been thinking about what happens if you have abundant code generation, and in, like-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... I, I think in all of our teams, agent-first engineering management and thinking about code quality is an unsolved problem.
- EGElad Gil
Yeah, and we'll get there. It'll be your teamwork, and we'll get there. What do you view as the major problems?
- SGSarah Guo
Um, w- well, the, the anxiety that I see, um, is like, if you can generate an enormous amount of code and no one is reading it, you don't know-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... the quality of the code. Nobody deeply understands the code base, and there's more fragility-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... right? It's like the slop problem, but instead of it being, like, vibe-
- EGElad Gil
Yeah
- SGSarah Guo
... coding slop for random websites for non-technical people-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... it's vibe coding slop in my actual production code base for every lazy engineer, which is every engineer. I think people are, like, looking at some problems of... I actually do think ticketing, ticketing systems are, are, like, at risk. But I think the broader problem that Jira could go solve or a new company goes, could go solve is, like, nobody knows-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... how to manage that issue of human attention to engineering, and there's a bunch of ideas-
- EGElad Gil
Mm, mm-hmm
- SGSarah Guo
... like testing and, like, you know, smart review, just let agents do it, formal verification. But I, I think it's like open season around this really, really big problem.
- 14:00 – 21:32
The Noise of the Last Month vs. Excitement
- SGSarah Guo
as well as a battle of how to produce code for a long time. So I, um, I feel like that has been missed a little bit, but I, I do think long run, the, the fundamental thing that the bottleneck on production of, you know, expensive-to-produce software, uh, being loosened is really cool, right? It just means, like, if you think of... There's a lot of embedded points of view in software on how to solve a problem, right?
- EGElad Gil
Mm-hmm.
- SGSarah Guo
You know, if it's engineering or, uh, enterprise sales, not a very software problem, or, or general productivity, right? Like, Notion is a way to do things. It's a building block system, but it's definitely got a, a point of view, and so if you reduce the cost to express that point of view in software, I think it's cool that we're gonna, like, see a lot more ideas.
- EGElad Gil
That's amazing.
- SGSarah Guo
Yeah.
- EGElad Gil
And again, I think it's a revolution, so don't get me wrong. I'm, I'm- I've been involved with coding companies really early on, and, um, I'm very excited about everything that's happening. And I think it's transformational, and I think it's revolutionary, and I think it's really important. I just think we had a month of kind of bullshit hype. [chuckles]
- SGSarah Guo
Okay, so if we ignore the noise-
- EGElad Gil
[chuckles]
- SGSarah Guo
... of the last month, where people got a little, like, frantic, what do you think is a signal that people are not paying attention to enough in such a noisy landscape? You were telling me that, like, growth, growth pace is, like, of the- of the biggest companies is, is still under- underpriced.
- EGElad Gil
Yeah. One thing that, um, Jared on my team put together that I thought was super interesting was, um, he pulled data from, uh, Capital IQ, where they just, like, predicted some projections on OpenAI and Anthropic, and they looked at, um... And then he sort of graphed out, and maybe we can share these graphs as part of this episode. He graphed out, um, how long it took different companies in years to go from a billion in revenue to ten billion dollars in revenue. So, for example, ADP took twenty-something years to grow from a billion to ten billion in revenue. And then the next wave of companies, like Adobe, took about twenty years to go from one to ten. And then you fast-forward in time, and you have things like Salesforce or SAP, sort of an even more modern cohort, and they took eight or nine years. Microsoft took, you know, seven-ish, eight years. Google and Meta and AWS took a couple of years, you know, three, four, or five years, but the AI labs did it in roughly a year, right? And then if you look at the projections, that, um-
- SGSarah Guo
It's a wild chart.
- EGElad Gil
Yeah. It's a wild chart, and so we should, we should add it, right? But you just see it go from, like, twenty-something years with Adobe to, like, a year for the AI labs. And then if you look at the projections that are sort of the public projections, they aren't necessarily the company-driven data, but the public projections on where the labs will end up, or how long it'll take them from, to go from ten to a hundred billion in revenue, for Microsoft, that was something like, uh, twenty-seven years. [chuckles] For Google, it was over a decade. Same with AWS, roughly the same for Meta, and then for the AI labs, it's like three, four, or five years. You know, it's very fast. And so we're seeing the fastest time to real massive revenue that we've ever seen in the history of software. It's just these insane curves, and again, we should post them. Part of that, I think, is just the internet has created this global pool of liquidity, and then suddenly every customer is online. It's much easier to distribute than it's ever been. So that's one piece of it. There's more people with access, there's higher GDP, there's lots of drivers for that. But then simultaneously, you're just creating enormous, um, business and user value at massive scale simultaneously, and these capabilities are so rich that you're seeing this take off in terms of revenue. And so it's, it's, it's unprecedented. It's really impressive, and I think people are ignoring the revenue and usage side of the equation. Um, the other thing that we actually put together was the collapse in token pricing for equivalent models. I think this was done initially by David, who worked for me, and then Shran. And so, for example, we looked at the cost of a GPT-4 level or equivalent model. Uh, we looked at that a year or two ago, and basically, in twenty-one months, it went from, like, thirty-seven bucks for a million tokens to twenty-five cents. And so, you know, pricing dropped by a hundred and fifty X in twenty-one months. And then we tried to extrapolate that curve, but obviously, people aren't really using GPT-4 level models anymore, [chuckles] even though, you know, they're two, three years old. And so we looked at o1 equivalent models, and the cost of a million tokens on an o1 equivalent model in December of twenty-four was about twenty-six bucks.... And then in November of twenty-five, it was thirty cents. So we saw another eighty-eight x drop, not eighty-eight percent or eighty- eight, you know, eighty-eight, eighty-eight times cheaper in eleven months for that next generation of models. So we're having pricing collapse on the token side, while we're having revenue ramp insanely on the usage side. And so that's insane if you think about that, just this pace of shift of cost, of revenue, of utilization, of everything. And this is back to, like, I'm incredibly bullish on everything that's happening. Um, and so it's more just modulating it against this, you know, this odd over extrapolation of what's actually happening, or actual capabilities, or, you know, what these things are really doing.
- SGSarah Guo
Yeah, I, I think one thing that people miss in the, like, bear case and all this stuff is, as you said, like revenue numbers, which is hard to miss. Um, but, but, uh, uh-- and then, um, uh, just like actual, um, like token inference count, right? If you look-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... at one-
- EGElad Gil
Insane.
- SGSarah Guo
If you look, where's the inference happening? It's either happening in inference clouds, right? Baseten, Model Fireworks, or it's happening at the pro- like, the very large model providers.
- EGElad Gil
All happening up here.
- SGSarah Guo
And it's happening in Elad's brain, which is still much more-
- EGElad Gil
And humans
- SGSarah Guo
... two magnitudes more efficient.
- EGElad Gil
And humanity in general.
- SGSarah Guo
Right.
- EGElad Gil
And humanity in general. Yeah. Yeah, it's true in terms of power utilization, the human brain is really impressive. What is it like? Tens of watts, twenty watts. How much-- Like, what's the power utilization of a human brain?
- SGSarah Guo
I'm gonna look it up right now. It is, it is-
- EGElad Gil
Something like that
- SGSarah Guo
... two magnitudes.
- EGElad Gil
It's like ten or twenty watts, I thought.
- SGSarah Guo
I think to the point of like, real data, the i- inference clouds are growing a thousand X in terms of consumption, right? And then they're getting more efficient, so revenue grows at some lower rate than that, but it's wild.
- EGElad Gil
It's twelve to twenty watts of power, which is comparable to a dim light bulb or a computer monitor in sleep mode. It's not- [chuckles]
- 21:32 – 23:20
What Proportion of GDP is Tech?
- SGSarah Guo
but then a series of the very best application companies. If they're growing to a billion of run rate rapidly, and valuations-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... grow in concert with that, then I, I do think there's a-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... there's a, a question on whether or not you, you, um, have the currency to compete, too.
- EGElad Gil
Yeah, I'm already seeing that in the SF housing market-
- SGSarah Guo
[chuckles]
- EGElad Gil
... right? Where, um, SF housing is starting to rise again, in part due to, um, I'm assuming outcomes from the lab tenders and things like that. Because suddenly you have these companies that are worth hundreds of billions of dollars out of nowhere in a few years, and as employees are selling into tenders, um, there's this new sort of influx of cash in the ecosystem. So and there's also Nvidia going from, you know, tens of billions or a hundred billion to trillions in market cap. Like, there's just this shift happening right now in terms of scale. There's an interesting question, actually, where, um, this is one other thing that we looked at as a team, and maybe I should just publish all these slides. We basically asked, um, what proportion of GDP is tech, right? And, and just the US economy at least, and how has that grown over time? And also, like, what has that meant in terms of market caps, right? And so if you look back to, uh, two thousand and five, Google was worth a hundred billion dollars, and Exxon was the world's most valuable company at four hundred billion dollars in market cap. And then, um, it took until twenty eighteen, Apple was the first company with a trillion-dollar market cap, right, ever. And everybody was shocked that anything could get to a trillion, and at the time, tech represented about thirty percent of the S&P. Um, before that, it was, say, you know, uh, ten percent-ish back in two thousand and five. And now the top eight tech companies are about twenty-three trillion of market cap,
- 23:20 – 25:02
Market Cap Shifts
- EGElad Gil
and they make up well over fifty percent of the S&P in terms of value. At the same time, um, they went from basically four percent of GDP in two thousand and five to about twelve percent of GDP today. And so then the question is, how, how-- what proportion of GDP eventually just becomes tech? And AI is a driver of this, right? Because you're taking services, and you're taking, uh, certain types of jobs, and you're augmenting them with AI, and you're converting them into effectively software spend or tech spend. And you can make different assumptions about growth rates, and then based on that, you know, you can end up with anywhere between fifteen, twenty percent of GDP to, you know, thirty percent of GDP in twenty thirty-five. But that means that the market caps of these tech companies get even bigger. You know, it's kind of a metric for how big can these things actually get as they sort of aggregate up portions of GDP. So I think that's the other lens that people aren't really thinking enough about in terms of what, what are, what are some of these terminal values ten years from now? Like, how much more can things grow, and what are your assumptions around that basis for growth, you know? And this is back to, like, that ramp-up into revenue. So it's a very interesting kind of set of questions that we're- we've been asking on my side.... just in terms of, like, these meta things, you know? Like, what are the, what are the bigger trends that people may not be paying attention to that may be super interesting?
- SGSarah Guo
Okay, well, then I have a set of, uh, structural questions about how to invest based on this for, for you, because, you know, asking for a friend, my funds are small. Um, I think there's, like, good implications and bad implications based on what you said. Like, one might be, if everything's gonna get a lot bigger, uh, a billion dollars is no longer late stage, right? That's, like, just, you know, take a marker on valuation, that it's like the beginning-
- EGElad Gil
Well, even now it's not late stage because people are raising a billion dollar valuation with two, two million in revenue, right?
- SGSarah Guo
Right. Well, you can decide that's a-
- EGElad Gil
I know of at least one
- 25:02 – 29:05
As a Company, When Should You Sell?
- EGElad Gil
company like that.
- SGSarah Guo
You can decide whether that's a, like a smart idea or not, right? But, um, but, you know, the, the point we would absolutely agree on, I think, is just, you know, the, the runway for some of these foundational companies is just much larger, right-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... um, than, uh, than the conventional wisdom.
- EGElad Gil
I think we've already believed that, though. Like, I think, um, everybody shifted- I remember I wrote a blog post, like, fifteen years ago or something, ten years ago, that basically talked about how hard it is to get to a sustainable five billion dollar market cap.
- SGSarah Guo
Mm-hmm.
- EGElad Gil
Because at the time, there was a sm-- basically, once every couple years, a company would actually get to that and stick with it. Because this is back to, you know, ten, fifteen years ago, the biggest market caps were in the hundreds of billions at most, and low hundreds of billions, right? And then we saw everything grow 10X over the last fifteen years, right? You suddenly have trillion-dollar market caps, and that means there's a lot more companies also worth a hundred billion than there used to be in tech. So I think in general, we've seen these shifts happening already, and that the reason that we were asking the question internally about how much bigger can these things get is because that has further implications. How many more trillion-dollar companies can be supported? Is it two? Is it three? Is it a dozen? Is it fifty? You know, um, and relatedly, like, if everything gets pulled up, how do you think about how you invest over the lifetime of a company in general? Or how do you think about that as a founder in terms of the, the end state? And then also, there's a related question of what's the actual fail rate of startups? Should the fail rate go up or down in that world? And you could argue it either way. You could argue that the fail rate should go up because more and more value is getting aggregated into platforms, like traditionally has happened, right? Every single platform shift has seen a commiserate, um, forward integration of that platform into the most important vertical application. So as an example, you know, Microsoft very famously on its OS, forward integrated into the Office suite, Excel and PowerPoint and Word, right? They killed or bought companies in those market segments, and that became Office, and then they redistributed it alongside the OS. Or Google forward integrated into vertical searches. They had a platform, and then they built out travel, and they built out local, and they built out all these things. And so it's not surprising that the labs will forward integrate into the most interesting applications. On top of them, you're already seeing that partially with code, but what else is coming there? And then what implication does that have for people running startups, right? Like, which of those verticals are, are durable and defensible, and which of those are gonna get eaten by the labs? And so, you know, you could make arguments in both directions in terms of, um, will more of overall GDP aggregate into a smaller number of companies, which is already what's happening, right? Just ignoring the labs even, right? That- that's kind of what happened with Amazon and with Google and all these things. Or do you end up with this broader tail effect as well, where things are kinda happen simultaneously? We also have a lot more startups that are worth more because there's just so much more market cap to go around, but also the internet continues to provide this global liquidity.
- SGSarah Guo
To me, um, uh, I think the tail dominates because, uh, the surface area of what you can address with technology is just increasing more rapidly. But, uh, maybe to add more nuance to, like, a billion dollars is-
- EGElad Gil
But is that true? So if you actually look at, um, market cap, it's very much power law, right? It's the head and torso aggregate almost all the value. That's actually true of customers, too, although people tend to misunderstand that. Um, even for things like Google, where the... There, there was, I remember the book that was like, "The Long Tail" or whatever, of the internet, and the claim was the long tail really matters, and then you'd add up Google's ad revenue, and you're like, actually, it's all the head and torso, right? And so I feel like there are these head and torso effects that keep getting ignored. It's like Paul Graham's power law on startups, right? Most of the value of YC is probably five companies, like eighty percent of it. I'm making it up-
- SGSarah Guo
Yeah
- EGElad Gil
... but it's really concentrated. And so why would that change in this era?
- SGSarah Guo
I don't, I don't think it changes in this era. I think that it depends on what your measure was. If your measure is how many hundred billion dollar businesses are there, I think there's a lot more, right? Like, it do- it doesn't mean there are fewer hundred billion dollar businesses.
- EGElad Gil
Mm-hmm.
- SGSarah Guo
Actually, there are more because the surface area is growing. And at the same time, like, the distribution of how much is in the head is probably the same,
- 29:05 – 30:45
Multi-Product Bundle Defense
- SGSarah Guo
and those are even bigger.
- EGElad Gil
Yeah, it's possible. Yeah, it's an interesting question.
- SGSarah Guo
Do you think for investing, like, there's a thing that's good for me, and then perhaps, like, bad for me, or just a question for the, for the, uh, continued growth stage investors. The time to market leadership and to revenue scale, I think, is compressing.
- EGElad Gil
Mm-hmm.
- SGSarah Guo
I mean, it's not, I think, like, this is happening. We have a large handful of companies that have gone zero to a hundred million plus run rate faster than SaaS companies that we'd seen ten years ago.
- EGElad Gil
Mm-hmm.
- SGSarah Guo
Um, and so valuations have grown with that. I think some set of companies that look like this, um, they are durable, and some, like, leadership can still flip, right?
- EGElad Gil
Mm-hmm.
- SGSarah Guo
Like, a question might be-
- EGElad Gil
Okay
- SGSarah Guo
... you know, is it you or is it Ant or is it OpenAI over time, to your point-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... of like, actually, you could grow to a billion dollars of revenue and still face that question.
- EGElad Gil
Mm-hmm.
- SGSarah Guo
Uh, and, and that is, I think, a risk that maybe some of the growth ecosystem would find as a new thing, versus like category leadership at a certain scale felt unassailable like ten years ago.
- EGElad Gil
Yeah, and I think there's two interesting historical precedents to this. One is the internet wave, where, you know, nineteen ninety-nine, four hundred and fifty companies went public, two thousand-- um, another four hundred and fifty went public. And so there was, say, one to two thousand companies went public during the internet age, and maybe a dozen to two dozen of them are still relevant, right? Everything else roughly died or got bought.... And then you fast-forward ten years, and you saw the subsumption of things that people thought were unassailable, right? In social networking, people thought Friendster and then MySpace were unassailable, and then Facebook won. In payments, I remember when I invested in Stripe, everybody said that, "Why are you doing this?
- 30:45 – 40:41
Conclusion
- EGElad Gil
You know, um, Braintree exists, and PayPal exists, and all these things exist, and so, you know, why would you ever invest in another payments company?" And, of course, that ended up being the winner, um, or one of the winners, right? I mean, payments is so big, it's a fragmented oligopoly. Um, but I just feel we've kind of seen this story before, and so as a founder, it's really useful to be asking about two things. One is, what is the durability of your business? And number two is, how should you think about when to exit if you're gonna exit? Because often for companies, there's about a twelve-month window where your company's the most valuable it will ever be, and then it crashes out. For a very small handful of companies, the answer is you should never, ever, ever sell. For most companies, the answer is you should sell when the timing is right, and then the question is, how do you know when the timing is right? Because ultimately, you're gonna hit a, a point of, of maximal value, and then it, and then it has a real potential to die, even if it got enormous traction, and that was the internet wave of the nineties. And so I think too few people are thinking about this, and one tip for founders is from a, a hygiene perspective, but also just a way to make it a non-emotional discussion, is pre-schedule once or twice a year the board meeting where you talk about exits, and that way it becomes non-emotional. It's not about we're gonna exit. It's not like we should exit. This has actually been Horace's advice, I think, um, from when he was running Opsware. You just set up a non-emotional meeting once or twice a year. You're like, "Nope, still not time to do it," or you say, "Oh, you know what? Actually, the competitive dynamic has shifted dramatically. Somebody's come to us with an offer that's higher than anything we'll achieve over the next five years. Now's the time to do it," right? And I think it's useful for you to be thoughtful about that, and again, the default for a small number of companies is never, ever do it. For almost everybody else, it's worth considering at one point or another because you may otherwise get stuck with something that isn't working for a long time, or you may get crushed by a competitor, and many, many years of very hard work can just go down the drain.
- SGSarah Guo
I think this is, uh, an interesting point about the comparison, especially to, like, the internet age versus the SaaS... I don't know what you call the, the, the, like, cloud age from the last decade as being more similar because there were-- I was not around for this era, but from, from my, um, research and from working with a bunch of people in that period, you're not old enough for this era either. Like, AOL was the internet for a moment, right? Yahoo! was the-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... web's front page. Netscape was the browser. Internet Explorer was the web runtime. eBay was the market. Like, I, I think there are a number of these-
- EGElad Gil
Yeah, and AOL exited at the exact right moment to Time Warner.
- SGSarah Guo
Right.
- EGElad Gil
At their peak, their peak valuation.
- SGSarah Guo
Right, and I, I do-- I think that people, founders and investors, may, um, over-rotate on the SaaS era, where, like, it did feel like at a certain scale... Um, like, internet era, there was a period of time where, like, growth was the default, right? Growth at a wild speed that was not true in SaaS land, and so it was more like, you know, incremental and beyond a certain scale, it felt very protected. But I, um, I think that this probably does look more like the internet era, where the question is, like, does that growth c-- like, does it compound to a control point where you're a very special company or, like, do you actually think about exits in a different way?
- EGElad Gil
Yeah, and, uh, if you even go back to the eighties, you know, you had Lotus. I don't know if you remember this company, Lotus.
- SGSarah Guo
I have implemented Lotus One Two Three at an enterprise business-
- EGElad Gil
Okay
- SGSarah Guo
... as an intern. [chuckles]
- EGElad Gil
Yeah, so- wow! So Lotus, uh, built one of the first spreadsheet products, and it grew explosively. It, it got into the hundreds of millions of revenue, like, really, really fast, and this was the eighties.
- SGSarah Guo
Yeah.
- EGElad Gil
Right? And then, a couple of years later, it basically collapses into the arms of IBM, and Microsoft launches Excel and takes the whole market, roughly, right? And so, again, it looked like a very durable business. It was the, the, the killer app on, on computers, you know, for its era, and then it just died. It didn't die. It, it ended up with a great exit to IBM, but still, it, it is, it no longer exists, right, in reality. And so I think the same thing is gonna happen for a number of companies of this era, and the question is, which companies? That's a really hard question, right? Who knows? But for some companies, you're starting to see cracks, right? And so the com- for the companies with these cracks, as the market structure shifts, as you see shifts in what the labs are doing, as you see shift in usage, as you see shift in differentiation and defensibility and all the rest, it's a good time to ask, "Hey, is this my moment? Are these next six months when I'm gonna be the most valuable I'll ever be, and then I'm at real risk?" And if so, you know, you should think seriously about what to do with that. And I, I view this not just, I mean, right now, I mean, every six months, there's gonna be these shifts that are worth considering, and that's why it's like pre-schedule the board meeting, so it's not emotional. You're not putting something on the agenda, and everybody's like, "Oh, my God, do you want to exit? What's going on? Are you upset? Are you worried?" It's more like, "Oh, yeah, we booked this six months ago, and we booked it a year ago, and we booked it two years ago," whatever it is, "and this is just when we talk about this stuff." So we can just have a very logical, emotion-drained conversation around this stuff.
- SGSarah Guo
And maybe, I, I think, you know, again, in comparison to internet era as to, like, why think about it more now is-
- EGElad Gil
Well, people in the internet era should have thought about it, too.
- SGSarah Guo
Sure, sure.
- EGElad Gil
I mean, Mark Cuban did this. Mark Cuban's claim to fame is he sold a, a company that, that, you know, let's, let's put it this way: it was early in terms of product, and he sold it to Yahoo! for a few billion dollars, and then he collared Yahoo! stock so that as the stock dropped, he didn't lose any money. It's one of the best all-time financial engineering moments in tech history, right? That's what made Mark Cuban a billionaire, was he sold at Yahoo!'s high-water mark, and then he kept all the value as it collapsed in price. That was one of the few people who did that, uh, during that era, but people were thinking about it.
- SGSarah Guo
I think, well, most people missed, right? Um, and, like, in retrospect, like, thinking about the flips that made it happen, where the ground was moving a lot, um, is useful-
- EGElad Gil
Mm-hmm
- SGSarah Guo
... right? Because you have to answer the question, "Am I that company or not?" Um, or, "Is my acquirer that company or not?" And, like, in the internet cycle, you had new distribution, new performance, new interfaces, changing user behavior.
- EGElad Gil
Mm-hmm.
- SGSarah Guo
It was just like-... everything happening all at once in new exploration. Not true in cloud land-
- EGElad Gil
Yeah.
- SGSarah Guo
-right? Just more replacement market, and then, like, niches that you could cheaply distribute to. New business model, SaaS is amazing.
- EGElad Gil
Yes.
- SGSarah Guo
Um, but in AI, it's like, okay, is, is the next major capability jump from the labs going to screw me and reset the leaderboard? Like, that is an important question to ask yourself.
- EGElad Gil
Mm-hmm.
- SGSarah Guo
And then also-
Episode duration: 40:41
Install uListen for AI-powered chat & search across the full episode — Get Full Transcript
Transcript of episode efUt__S_AjY
Get more out of YouTube videos.
High quality summaries for YouTube videos. Accurate transcripts to search & find moments. Powered by ChatGPT & Claude AI.
Add to Chrome