Y CombinatorVertical AI Agents Could Be 10X Bigger Than SaaS
EVERY SPOKEN WORD
40 min read · 8,392 words- 0:00 – 1:01
Coming Up
- HTHarj Taggar
Every three months, things have just kept getting progressively better, and now we're at this point where we're talking about full-on vertical AI agents that are going to replace entire teams and functions and enterprises. That progression is still mind-blowing to me.
- DHDiana Hu
A lot of the foundation models are kind of coming head-to-head. There used to be only one player in town with OpenAI, but we've been seeing in the last batch this has been changing.
- GTGarry Tan
Thank God. (laughs) I was like, competition is, you know, the soil for a very fertile marketplace ecosystem, uh, for which consumers will have choice, and, uh, founders have a shot, and that's the world I want to live in. Welcome to another episode of The Light Cone. I'm Garry. This is Jared, Harj, and Diana. And collectively, we funded hundreds of billions of dollars worth of startups right when they were just one or two people starting out. And today,
- 1:01 – 7:25
Jared is fired up about vertical AI agents
- GTGarry Tan
Jared is a man on fire, and he's gonna talk about vertical AI.
- JFJared Friedman
Yes, I am. I am fired up about this because I think people, especially startup founders, especially young ones, are not fully appreciating just how big vertical AI agents are going to be. It's not a new idea. Some people are talking about vertical AI agents. We funded a bunch of them, but I think the world has not caught onto just how big it's going to get. And so I'm going to make the case for why I think there are going to be $300 billion-plus companies started just in this one category.
- HTHarj Taggar
Nice.
- JFJared Friedman
I'm going to do it by analogy with SaaS, and I think in a s- in a similar fashion, people don't understand just how big SaaS is because most startup founders, especially young ones, tend to see the startup industry through the lens of the products that they use as a consumer. And as a consumer, you don't tend to use that many SaaS tools because they're mostly built for companies. And so I think a lot of people have missed the basic point that if you just look at what Silicon Valley has been funding for the most, for like, for the last 20 years, like, we've mostly been producing SaaS companies, guys. Like that's literally been like most of what has been coming out of Silicon Valley. It's over 40% of all venture capital dollars in that time period went to SaaS companies, and we produced over 300 SaaS unicorns in that 20-year time period, which is way more than every other category.
- GTGarry Tan
Software's pretty awesome.
- HTHarj Taggar
Yep.
- JFJared Friedman
Software is pretty awesome. I was thinking back to the history of this because, you know, we, we always like to talk about the, sort of how the, how the history of technology informs the future. And, um, the, the real catalyst for, for the SaaS boom was, uh, do you guys remember XMLHTTPrequest?
- GTGarry Tan
(laughs) Oh my God.
- JFJared Friedman
Like I'd, I'd argue that that was quite literally the catalyst for the SaaS boom.
- GTGarry Tan
Like, uh, AJAX?
- JFJared Friedman
AJAX, yeah. In 2004, browsers added this JavaScript function XMLHTTPrequest, which was the missing piece that enabled you to build a rich internet application in a web browser. So, for the first time, you could make things in websites that looked like desktop applications, and then that created Google Maps and Gmail and set up this whole, like, SaaS boom. Essentially, the, the key technology unlock was that software moved from being a thing that you got on a CD-ROM and installed on your desktop to being something that you use through a website and on your phone.
- GTGarry Tan
Yeah. Paul Graham actually, uh, shares in that lineage in that he was one of first people to realize that he could take the HTTP request and then actually hook it up to a Unix prompt, and you didn't actually have to, you know, have a separate-
- JFJared Friedman
Yeah.
- GTGarry Tan
... computer program-
- JFJared Friedman
Yeah.
- GTGarry Tan
... that would change a website. So Viaweb was a, uh, online store, kind of like Shopify, but way back in the day.
- JFJared Friedman
Yeah, it was basically like the first SaaS app ever.
- GTGarry Tan
Right.
- JFJared Friedman
Like, like, PG actually invented SaaS in, like, 1995. It's just that those first SaaS apps kind of sucked because they didn't have XMLHTTPrequest. And so every time you would, like, click a button, it would have to reload the whole page. (laughs) And so it was just a shitty experience, and so it didn't really catch on until 2005 when X- XMLHTTPrequest widespread. Anyway, I, I see this LLM thing as, like, actually very similar. Um, it's like it's a new computing paradigm that makes it possible to just, like, do something fundamentally different. And in 2005, when cloud and mobile finally took off, there is this sort of, like, big open question of, like, "Okay, well, this new technology exists. What should you do with it? Where is the value going to accrue? Where are the good opportunities for startups?" I was going through the list of, like, all the billion-dollar companies who were created, and I kind of had this realization that, um, you could kind of bucket the, the different paths that people took into, like, three buckets. Um, there's, there's a first bucket that people started with, which was, like, I would call them obviously good ideas that could be mass consumer products. Um, so that's like docs, photos, email, calendar, chat, all these things that, like, we used to do on our desktop, but that obviously could be moved to the browser and to mobile. And the interesting thing is zero startups won in those categories. 100% of the value flowed to incumbents, right? Like Google, Facebook, Amazon, they own all, all those businesses. Folks forget that, like, Google Docs wasn't the only company that tried to bring Microsoft Office online. There were, like, 30 companies that tried to bring Microsoft Office online, but they all lost. Google won. Then there was, like, a second category, which was, like, mass consumer ideas that were not obvious that nobody predicted. Um, that's like Uber, Instacart, DoorDash, Coinbase, tho- Airbnb.
- GTGarry Tan
New marketplaces.
- JFJared Friedman
Those ones, those ones came out of left field like the, the dot-dot-dot between XMLHTTPrequest and Airbnb is, like, very not obvious. (laughs)
- HTHarj Taggar
Yeah.
- JFJared Friedman
And so the incumbants didn't even try competing in those spaces until it was, like, too late. And so startups were able to win there. And then there's a third category, which is all the B2B SaaS companies, and that's, like, 300 of them. And so, like, mo- Like, by, by, by number of logos, way more billion-dollar companies were created in that third category than the first two. I think one reason why that happened is, like, there is no...... like Microsoft of SaaS. Like, there is no company that somehow does, like, SaaS for, like, every vertical and every product. Like, for structural reasons, it seems to be the case that, like, they're all different companies and that's why there's so many of them.
- HTHarj Taggar
I think Salesforce is probably, like, the first true SaaS company.
- JFJared Friedman
Mm-hmm.
- HTHarj Taggar
Um, and I, I remember Marc Benioff coming to speak at YC and he tells a story. It's just very early on. People just didn't believe you could build sophisticated enterprise applications, like, over the cloud or via SaaS.
- JFJared Friedman
Yeah.
- HTHarj Taggar
It was just so, um ... There was just, like, a perception issue, right? It was like, no, like you don't, you buy, like, your box software and that's, like, the real software that you run your-
- GTGarry Tan
This is the way we always do it.
- JFJared Friedman
It was, it was quite contrarian 'cause the early web apps sucked.
- 7:25 – 9:09
The parallels between early SaaS and LLM’s
- JFJared Friedman
And so when I think about the parallels with LLMs, I could easily imagine this same thing happening, which is that there's a bunch of categories that are like mass consumer applications that are obviously huge opportunities, but probably the incumbents will win all of those. So that's something like a pur- like a general purpose AI voice assistant that you, you know, you can ask it to do anything and it'll, like, go do that thing. That's an obvious thing that should exist, but, like, all the big players are going to be competing to be that thing, right?
- GTGarry Tan
Wow. Apple's a little slow on that one.
- JFJared Friedman
(laughs)
- GTGarry Tan
And why is Siri so stupid still?
- JFJared Friedman
(laughs) Yeah.
- GTGarry Tan
What year is it? It makes no sense.
- HTHarj Taggar
(laughs) I mean, it's interesting. Like, a counter to that is, like, the very obvious thing is search. And maybe Google will still win, um, on search, but Perplexity is definitely give them a-
- JFJared Friedman
Give them a run for their money.
- HTHarj Taggar
... huge run for their money, right? (laughs)
- JFJared Friedman
Totally.
- GTGarry Tan
Yeah, this is the classic innovator's dilemma at the end of the day. I mean, you could argue, going back to what you said about Uber or Airbnb, these were actually really risky things from a regulatory standpoint.
- JFJared Friedman
Yeah.
- GTGarry Tan
So if you're Google and you have basically a guaranteed, you know, giant, uh, pot of gold that, you know, sort of comes to you every single month, like, why would you endanger that pot of gold to sort of pursue these things that, uh, might be scary or might ruin the pot of gold?
- JFJared Friedman
I think Google
- JFJared Friedman
I think that's a n- I think that's, like, probably the primary reason why the incumbents didn't end up building those products and didn't even clone them, even after they got big and it was obvious th- that they were going to work. Google never launched an U- an Uber clone. They never launched an Airbnb clone. Um, I was listening to this, uh, talk by Travis, and one of the things that he said that really stuck with me is that in the, in the first years of Uber, he was very scared that he was going to personally go to prison for like a long time. (laughs) Like, he was actually personally risking going to prison in order to build that company. And so yeah, no highly paid Google exec was going to do that.
- 9:09 – 12:25
Why didn’t the big companies go into B2B SaaS?
- JFJared Friedman
(laughs) What do you think about, um, why the incumbents didn't go into B2B SaaS? Is it part of the reason is that a lot of the use cases are very ... There's a very wide distribution?
- JFJared Friedman
I ... It's a great question. I love to hear what you guys think. My take is that it's just too hard to do that many things as a company. Like, each B2B SaaS company really requires, like, the people who are running the product and the business to be extremely deep in one domain and care very deeply about a lot of really obscure issues. You know, like, take like Gusto, for example. Like, why didn't Google build a Gusto competitor? Well, there's no one at Google who really understands payroll and has the patience to, like, deal with all the nuances of all these, like, stupid payroll regulations. (laughs) And, like, it's just like, (laughs) like, it's just not worth it for them. It's easier for them to just focus on, like, a few really huge categories.
- HTHarj Taggar
In the B2B SaaS world, it's, it's sort of about the unbundling, bundling of software argument that comes up a lot as well, I think, and why didn't, why did all these vertical B2B SaaS products evolve versus just, like, Oracle or SAP or, um-
- JFJared Friedman
NetSuite.
- HTHarj Taggar
Yeah, NetSuite. Just owning, like, everything. Um, and I think it might be als- is another thing that's attributable to the shift to, like, SaaS and the internet is in the old ways of selling software, again, like, you had this box software that was really, like, expensive to install and you had, like, a whole ecosystem around it, and anytime you wanted something custom, like, the integrators would just say, "Oh, no." Like, "We can, like, just build you a custom, like, payroll feature," or something like that. And then Salesforce comes along with, like, a SaaS solution and it just seems like it could never be as powerful or sophisticated as, like, the expensive enterprise installation you just paid for. But they proved that it totally was the case, and I think that just, like, opened the gates for all of these, like, vertical SaaS solutions to emerge doing exactly what you're saying.
- JFJared Friedman
I guess the other problem is that with a lot of this enterprise software, if you're a user of Oracle and a NetSuite, because they're, they have to cover so much ground, the user experience is actually pretty bad. They're trying to be jack of all trades, but master of none.
- HTHarj Taggar
Yep.
- JFJared Friedman
So it b- ends up being a bit of a kitchen sink type of experience. And this is where if you go and build that B2B SaaS vertical company, you could do literally a 10 X better experience and more delightful because there's this stark difference between consumer products and enterprise user experience.
- HTHarj Taggar
Yeah.
- GTGarry Tan
Well, there's only, uh, what? Three price points in software. It's, uh-
- JFJared Friedman
(laughs)
- GTGarry Tan
... $5 per seat, $500 per seat, or $5,000 per seat. (laughs) And, uh, that maps directly to consumer SMB or enterprise sales. And then I think time immemorial has taught us that in the past, and this is less and less true, uh, with new software thankfully, but enterprise is terrible software because it's not the user buying it. You know, some high up mucky-de-muck inside a Fortune 1000 is the person who's getting wined and dined for this, you know, mega seven-figure contract and, you know, they're-... going to choose something that maybe isn't that good, actually, for the end user, the person who has to actually use the software day-to-day. And, um,
- 12:25 – 16:25
How employee counts might change
- GTGarry Tan
I'm sort of curious to see how this changes with LLMs, actually. I mean, to date, one of the more salient things that we've seen for both SMB and enterprise software companies is that... Or all software companies, all startups, period, is like, you know, there's a sense that as revenue scales, the number of people you have to hire scales with it. And so, when you look at unicorns, uh, even in today's YC portfolio, uh, it's quite routine to see a company that reached 100 or $200 million a year in revenue, but they have like 500, 1,000, 2,000 employees already. And I'm just gonna be very curious, like, uh, even the advice that I'm starting to give companies that are, you know, a month or two out of the batch, uh, it's, uh, it's feeling a little bit different than the kind of advice I would give last year or two years ago. In the past, you might say, you know, "Let me find the absolute smartest person, uh, in all of these other parts of the org, like customer success or sales or different things like that. And, uh, I want to find someone who I've worked with, who is, I know is great, and then I'm going to go sit on their, you know, uh, uh, on their doorstep until they quit their jobs and come work for me."
- JFJared Friedman
(laughs)
- GTGarry Tan
"And I want them to be someone who can, you know, build a team for me, hire a lot of people." That might still be true, but I'm starting to sense that, uh, the meta shifting a little bit. Like, you actually might want to hire more really good software engineers who understand large language models, uh, who can actually automate the specific things that you need that are the bottlenecks to your growth. And so it might result in, you know, a very subtle but, you know, significant change in the way startups grow their businesses, sort of post-product market fit. It means that I'm going to build LLM systems that bring down my cost, that cause me not to have to hire a thousand people. I think we're right at the beginning of that revolution right now.
- DHDiana Hu
I mean, we talked about this in a previous episode. We talked about there will be a future unicorn company that's only run, if we take it to the limit, with only 10 employees. That's completely plausible.
- GTGarry Tan
And they're writing the evils and the prompts.
- DHDiana Hu
That's it. (laughs)
- HTHarj Taggar
I think what you're saying is like a trend that was already underway pre-LLMs. Like, I remember when I was running Triplebyte, for example, we needed to, like, build marketing or custo- like user acquisition basically, um, and especially after we raised our series B, the, like, traditional way you were supposed to do that is to, like, hire a marketing executive and build out, like, a marketing team and, um, and just, like, basically spin up this machine to do, like, sales and marketing. But I'd actually met, like, a YC founder, um, Mike, who was... His company was basically building, like, a smart frying pan. Sounds, like, bizarre, but, like, he was a MIT engineer.
- GTGarry Tan
I remember.
- HTHarj Taggar
Yeah, you remember this? Um, he's an MIT engineer, and to sell the smart frying pan-
- DHDiana Hu
(coughs)
- GTGarry Tan
Awesome.
- HTHarj Taggar
... he had to get really, really good at understanding, like, paid advertising and, um, uh, Google Ads and just a whole bunch of stuff. And so he, he'd taken this engineer's mindset approach to it, and I remember just talking to him about it, and realizing this would be so much better to have an MIT engineer working on, like, our marketing efforts than any of the marketing candidates I've spoken to. And he was able to, like, scale us up to, like... I mean, we were spending, like, at one point, like, a million dollars a month on just marketing and various, like, campaigns.
- JFJared Friedman
And, and Triplebyte had great marketing.
- HTHarj Taggar
Yeah.
- JFJared Friedman
Like, I remember, like, the Caltrain-
- HTHarj Taggar
Yeah.
- JFJared Friedman
... station takeover that you did, all the, like, out of home stuff that you did, it was, like, really high-quality stuff. It stuck with the... You could tell that it was not being done by some, like-
- HTHarj Taggar
Yeah.
- JFJared Friedman
... VP of marketing person.
- HTHarj Taggar
And, th- um, and that was all Mike. And, like, the comment I would often get when people would ask me around that time, like, "How big is Triplebyte?" And we were like, "50 people." And I would be able to be-
- JFJared Friedman
It felt so much better. (laughs)
- HTHarj Taggar
Yeah, yeah. People would be like, "Oh, there's like, uh, hundreds of people." I was like, "No, it's all because if you put a really smart engineer on some of these, like, tasks, they just find ways to make..." They find leverage. And now, like, LLMs can go even way beyond, like, the leverage you had with just pure software.
- 16:25 – 21:31
The argument for more vertical AI unicorns
- JFJared Friedman
Okay, so here's my pitch for 300 vertical AI agent unicorns. Literally every company that is a SaaS unicorn, you could imagine there is a vertical AI unicorn equivalent in, like, some new universe. 'Cause, like most of these SaaS unicorns, beforehand, there were some, like, box software company that was making the same thing that got disrupted by a SaaS company. And you could easily imagine the same thing happening again, where now basically every S- every SaaS company builds some software that some group of people use. The vertical AI equivalent is just gonna be the software plus the people (laughs) in one product.
- HTHarj Taggar
One thing might be just enterprises, in general, right now are a little unsure about what exactly they, like, what agents they need. And one approach I've seen from especially more experienced founders like, um, Brett Taylor, the CTO of Facebook, started this company, Sierra. I don't know all the details, but as far as I can tell, it's essentially more, like, broadly about letting enterprises, like, deploy these AI agents and spinning them up, like, custom for the enterprise versus like, "Oh, hey, we have, like, this specific agent to do this." It's something I've seen from one of my companies called, um, uh, Vectorshift that we funded about a year ago. They're two really smart, like, Harvard computer scientists, and it's a, they're... What they found is that they're trying to build a platform to make it easy for enterprises to build their own, like, use, like, no code or SDKs to build their own, like, um, internal LLM-powered agents. But, like, enterprises often don't know exactly what they want to use these things for. And so, bringing it back, I wonder if, like, in, like, the box software world, you started off with just, like, a few vendors who just basically were trying to convince people to use software at all-
- JFJared Friedman
Yeah.
- HTHarj Taggar
... and it was just like, it does everything, um, and then it gets more sophisticated and higher resolution and you get lots of, like, vertical SaaS players. Will we go through that same period with LLMs, where the early winners might just be these, like, general purpose, "Hey, like, we'd like make it easy for you to do LLM stuff," and then it...... the vertical agents will come in over time, or do you think there's reasons it's different now and the vertical agents will take off on day one?
- JFJared Friedman
Yeah, that's interesting, 'cause if you think about the history of SaaS, the consumer things worked first. Like, 2005 to 2010 was mostly consumer applications like email and chat and maps, and people got, y- people, uh, as individuals, got used to using these tools themselves, and I think that made it easier to sell SaaS tools to companies because, you know, the same people are both employees and consumers.
- HTHarj Taggar
Yeah. I, I think the answer might just be, like, this is, this is all just a continuation of software and just there's no reason it has to reset back. Like, LLMs don't have to reset back to a few general purpose, like, enterprise LLM platforms doing everything, because enterprises have already been trained on, like, the value of point solutions and vertical solutions. Um, and, like, the user experience is not going to be that different. These things will just be a lot more powerful. And so, if enterprises have already built the muscle of believing that, like, startups or vertical solutions can be better than, like, legacy broad platforms, they are probably going to be willing to take a bet on a startup promising a very good vertical AI agent solution today. And I feel like we're all seeing that in the batch now, where some of our companies are getting faster traction in enterprises for these vertical AI agents than, like, we've ever seen before.
- GTGarry Tan
I think we're just early in the game, right? Like, all software sort of starts quite vertical, and then as the industries actually get much more developed, um, then... I mean, I just answered my earlier question. It's like, you know, why does a company end up having a thousand employees? It's actually that, uh, you know, early, early in the game, everyone's making these specific point solutions, and then at some point, you've got to go horizontal. Like, you're already doing this crazy spend on sales and marketing, and then the only way you can actually continue to grow once you sort of get 100% or, you know, some large majority of the market, is you actually have to do, like, not just a point solution, but things that sort of work together.
- DHDiana Hu
I mean, the other point of why the bull case for vertical AI agents could be even bigger than SaaS is that SaaS, you still needed a operations team or set of people to operate the software in order to get all the workflows to be done. I don't know, approval workflows or you have to input the data. The argument here is that you will get not only replacing all that set of SaaS software, so that will be like one-to-one mapping, but it's also going to eat all of the, a lot of the payroll.
- JFJared Friedman
Totally.
- DHDiana Hu
Because you look a lot of the spent for companies, big chunk is still a payroll and software's tiny.
- JFJared Friedman
Exactly. They spend way more on employees than they do on software. (laughs)
- DHDiana Hu
So it'll be these smaller companies that are way more efficient, that need way less humans to do random data entry or approvals or click the software.
- JFJared Friedman
I agree. I think it's very possible that the vertical equivalents will be 10 times as large as the SaaS company that they are disrupting.
- GTGarry Tan
Yeah.
- DHDiana Hu
I mean, there's, there's two case. It could be that the vertical point solution could be just big enough and you don't need to do that bra- breadth thing, right? It- that could be another scenario.
- 21:31 – 35:22
Current examples of companies/uses
- JFJared Friedman
Should we give some examples? I feel like we've all been-
- HTHarj Taggar
Now's a good time to talk about some.
- JFJared Friedman
... working with so many verticals AI agent companies, we've got, like, news from the front-
- HTHarj Taggar
Yeah.
- JFJared Friedman
... of (laughs) like-
- DHDiana Hu
(laughs)
- JFJared Friedman
... how it's actually going.
- GTGarry Tan
Well, your former, uh, head of product, Aaron Cannon, is working on a YC company called Outset that I worked with and, uh, basically they're taking LLMs, uh, to the surveys and Qualtrics space. So Qualtrics is almost certainly not really going to build the best of breed, uh, large language model with reasoning. And then the funny thing about surveys is, you know, who's it actually for? It's for people who run products, for marketing teams, it's for people who are trying to make sense of, like, what do our customers actually want, and what are surveys? Like, guess what? That's language. So, um, and then I feel like these types of businesses, um, actually have to thread this needle, um, because enterprise and SMB software often is sold based on a particular person who is the key decision maker, and, um, you have to go high enough in the organization so that the people you're selling to are not afraid that their whole, their job and or their whole team's job is going to go away.
- DHDiana Hu
Totally.
- JFJared Friedman
Yeah.
- DHDiana Hu
That's kind of the move that I seen that a lot of companies that sell need to do, because if you're going to go and sell to the team that's going to get replaced by AI-
- GTGarry Tan
Oh yeah, they're going to sabotage it, man.
- JFJared Friedman
(laughs)
- HTHarj Taggar
Yep.
- DHDiana Hu
It just does not work.
- GTGarry Tan
Yeah.
- DHDiana Hu
So I think this is a interesting way that a lot of these are top down and you have to go through, at some point even get the CEO to sign off on it.
- HTHarj Taggar
A company I'm working with, uh, Momentic, that's sort of, uh, essentially an AI agent, but for at least where they're starting as like QA testing, um, they're actually getting really great traction right now. And it's interesting because you remember a decade ago, um, YCombinator we worked with Rainforest QA. Like, Rainforest was a QA as a service company, and that they had this exact tension of where they couldn't actually replace your QA team, and so they needed to build software that made the QA team more, like, efficient, but really that obviously meant trying to replace as many of them as possible. They couldn't replace the whole team, and so they were always on this sort of, like, tightrope between trying to sell the software to, like, the head of engineering-
- JFJared Friedman
(laughs)
- HTHarj Taggar
... and said this will mean you'll need less QA people, and great, but then you also have to go sell that to the QA team who don't want to be replaced. And so I think that was always, like, a friction for that business for how it could, like, scale and grow. But now, like, Momentic with AI can actually just replace the QA people. So their pitch is not, oh, this, like, makes your QA people faster, it's like, this just means you don't need a QA team at all, so you can just focus the sale onto, like, engineering and engineering doesn't need buy-in from QA at this point. And you can also go in... I mean, to start with, you can go and sell to companies that don't even have big QA teams at the moment, they just use something like Momentic and then it will just, like, keep scaling with them.
- JFJared Friedman
Scaling and they'll just never build a QA team-
- HTHarj Taggar
Yeah.
- JFJared Friedman
... ever.
- HTHarj Taggar
Yeah.
- JFJared Friedman
Yes. That is a real life case study of what Diana was saying about why these vertical AI agent companies can be 10 times as big as the SaaS companies.
- HTHarj Taggar
Yeah. I'm seeing this interesting now, um, like in recruiting too. I had this exact same issue with
- SPSpeaker
Oh.
- HTHarj Taggar
... Triplebyte-
- JFJared Friedman
(laughs)
- HTHarj Taggar
... where to build a software, um, to build software that makes it easy to, like, screen and hire software engineers you need buy-in from both the engineering team that they're joining, but also their recruiting team, and effectively the software we were building was trying to replace the recruiters, but we couldn't completely replace the recruiters. But now within YC there's-
- 35:22 – 40:04
AI voice calling companies
- JFJared Friedman
Do you guys want to talk about some of the voice companies that we have? I think that's like an interesting, like subcategory of this, of this stuff that's like really blowing up now.
- DHDiana Hu
I have a company that I work with called Salient that basically does AI voice calling to automate a lot of debt collection in the auto lending space, which traditionally-
- JFJared Friedman
So they like call up people and are like, "Hey, you owe $1000 on your car."
- DHDiana Hu
Yeah. Which actually-
- JFJared Friedman
"What's up with that?"
- DHDiana Hu
Actually this kind of job is one of those butter passing job. It kind of sucks because a lot of, uh, these low wage workers work in all these call centers and it's like a terrible boring job, so very high churn and giant headcount to run these because there's just so many accounts with these banks that have to do that. And this is a perfect task that AI could automate. And what Salient has done is, has been able to actually get very, very accurate and it has been going live with a lot of big banks, which is super exciting. And this was a company from last year and demonstrating that, that part of it that they were able to get in because they sold through top down.
- GTGarry Tan
I guess the space feels like it's moving very quickly and that we have incredible companies that are voice infra companies like Vapi and then people can sort of get started right away. And retail also. I mean, these are companies that have reached pretty fast scale just because it's one of the more exciting, like mind-blowing things that you can get up and running within, I mean, literally the course of hours. Um-And then some of the question that, you know, remains unanswered, and we hope they figure it out, is how do you hold onto them? Especially as you, uh, run into things like the new OpenAI voice APIs. Um, you know, do you go direct? Like, you prob- it's probably way more work to try to use the underlying APIs off the bat, but these, uh, platforms are clearly low-bar. And then the question is can you keep raising the ceiling so that you can hold onto customers forever?
- JFJared Friedman
Harj, you were making an interesting point earlier about, like, how the apps that people have built on top of LMs has changed from like early 2023 when it started until now.
- HTHarj Taggar
Yeah. Voice, which we were just talking about, is a great example of this. I think even if you went six months back, it felt like the voices were not realistic enough yet. The latency was too high. Like, there was n- it felt like we were probably a ways off having AI voice apps that could meaningfully, like, replace, like, humans calling people up, and, like, here we are. And yeah, we're just sort of zooming out, thinking back to the first YC batch where LLM-powered apps first came in. It was probably winter 2023, you know, almost two years ago now. And the apps were essentially just things that spat out some text, and not even, like, perfect text.
- GTGarry Tan
The rocks could talk, that's about it.
- HTHarj Taggar
Yeah, right?
- DHDiana Hu
Sort of more like copyediting, marketing edit-
- HTHarj Taggar
Yeah.
- DHDiana Hu
... email edits. It was just kind of more, like, just like incremental.
- HTHarj Taggar
Yeah. Like I rem- I had a company... I mean, the one that sticks in my head is a company called Speedy Brand. And all, what they did is make it very easy for, like, a small business to just generate a blog and spit out content marketing. Um, it was like a very obvious idea. And it wasn't perfect, but it was pretty cool at the time. And that's when, we talked about it a bunch on the show, but that was like, the ChatGBT wrapper turned out around that time. So hey, like, this is what an LLM app looks like, it's just a ChatGBT wrapper. It does very basic, spits out some text. Like, it's going to get crushed by OpenAI in the next release. Like-
- JFJared Friedman
And it did.
- HTHarj Taggar
(laughs) Yeah.
- JFJared Friedman
Well, I don't, I don't, I don't know if-
- HTHarj Taggar
No, Speedy-
- JFJared Friedman
... that one did, but, but the, that, that first, that first wave of LLM apps mostly did get crushed by the next wave of-
- HTHarj Taggar
Right.
- JFJared Friedman
... GPTs, yeah.
- HTHarj Taggar
But I, I feel like we've had this sort of boiling of the frog effect, where from our perspe- it's sort of like every three months things have just kept getting progressively better. And now we're at this point where we're talking about, like, full-on vertical AI agents that are going to replace entire teams and functions and enterprises. Um, and just that progression is still mind-blowing to me. Like, we're two years in, which is still relatively early, and the rate of progress is just, like, unlike anything we've seen before.
- DHDiana Hu
And I think what's interesting to see is, we discussed this in the last episode, is a lot of the foundation models are kind of coming head-to-head. There used to be only one player in town with OpenAI-
- JFJared Friedman
Mm-hmm.
- DHDiana Hu
But we've been seeing in the last batch this has been changing. Claude is a huge contender.
- GTGarry Tan
Thank God. (laughs) Is like, competition is, you know, the, the soil for a very fertile marketplace ecosystem, uh, for which consumers will have choice and, uh, founders have a shot. And that's the world I want to live in. So people
- 40:04 – 41:36
What is the right vertical for you as a founder?
- GTGarry Tan
are watching and thinking about starting a startup or maybe have already started and, uh, they're hearing all of this. How do you know what the right vertical is for you?
- HTHarj Taggar
You got to find some boring, repetitive admin work somewhere. And that seems to be just like the common thread across-
- JFJared Friedman
Yes.
- HTHarj Taggar
... all of this stuff, is if you can find a boring, repetitive admin task, um, there is likely going to be a billion dollar AI agent startup if you keep digging deep enough into it.
- GTGarry Tan
But it sounds like you should go after something that you directly have some sort of experience or relationship to.
- HTHarj Taggar
That is a common, like, that is definitely a common thread I've seen in the companies that are, that I'm seeing promise with. And another one just pops into my head, Sweet Spot. I think I mentioned on this before, like, they're basically building an AI agent to bid on government contracts. And the way they found that idea, and this is a year ago, was they just had a friend whose full-time job was to sit there on like a government website, like refreshing the page, like looking for new proposals to bid on. And they, they were pivoting and they're like, "Oh, like, that seems like something an LLM could do." Um, a company from a recent batch which pivoted into a new idea that's getting great traction, like, they're basically building an AI agent to do, um, processes like medical billing for dental clinics. And the way they found the idea was, um, one of the founder's mothers is a dentist, and so he just decided to go to work with her for a day and just sit there seeing what she did. And she's like, "Oh, like, all of that, like, processing claims seems like really boring. Like, an LLM should totally be able to do that." And he just started writing software for, like, his mother's dental clinic.
- 41:36 – 42:12
Outro
- GTGarry Tan
So I guess, I mean, in robotics, the classic maxim is, uh, you know, the robots that are going to be profitable and that are going to work are going to be, um, dirty and dangerous jobs. And in this case, for vertical SaaS, look for boring, butter-passing jobs. (laughs)
- HTHarj Taggar
(laughs) Yeah.
- GTGarry Tan
Well, with that, we're out of time for today. We'll catch you on the light cone next time.
Episode duration: 42:12
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