Vertical AI Agents Could Be 10X Bigger Than SaaS
Harj Taggar (host), Diana Hu (host), Garry Tan (host), Jared Friedman (host), Jared Friedman (host)
In this episode of Y Combinator, featuring Harj Taggar and Diana Hu, Vertical AI Agents Could Be 10X Bigger Than SaaS explores vertical AI Agents Poised To Eclipse SaaS And Reshape Workforces The hosts argue that vertical AI agents—AI systems tailored to specific business functions—could produce at least 300 new billion‑dollar companies, potentially becoming 10x larger than today’s SaaS winners because they replace both software and headcount.
Vertical AI Agents Poised To Eclipse SaaS And Reshape Workforces
The hosts argue that vertical AI agents—AI systems tailored to specific business functions—could produce at least 300 new billion‑dollar companies, potentially becoming 10x larger than today’s SaaS winners because they replace both software and headcount.
They draw historical parallels between the rise of SaaS (enabled by browser tech like XMLHttpRequest) and the current LLM wave, emphasizing that most value in the last era accrued to B2B vertical tools rather than obvious consumer apps.
Vertical AI agents are already gaining traction in domains like QA testing, recruiting, customer support, developer relations, call centers, surveys, and medical/dental billing by fully automating previously human‑heavy workflows.
The conversation explores why incumbents rarely dominate vertical software, how AI may change company scaling and org design, and how founders should identify promising verticals by targeting boring, repetitive administrative work they understand deeply.
Key Takeaways
Vertical AI agents can subsume both software and the human teams operating it.
Where SaaS replaced boxed software but still required large ops teams, AI agents combine the app plus the work of the people using it, allowing companies to eliminate entire functions like QA, recruiting screens, or call-center agents.
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The SaaS playbook suggests hundreds of vertical AI unicorns are plausible.
Over 300 SaaS unicorns emerged as software moved to the browser; the hosts argue each major SaaS category (e. ...
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Incumbents are poorly positioned to win most vertical AI categories.
Deep domain knowledge, focus, and willingness to overhaul existing products are required for each niche; big tech firms rarely invest in the obscure details and organizational risk needed to dominate many narrow domains.
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Founders should chase “boring, repetitive admin work” they know firsthand.
The most promising verticals often emerge from observing mundane, high-volume processes—like medical billing, government RFP bidding, or survey analysis—especially where someone’s full-time job is structured, language-heavy grunt work.
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AI will change how startups scale and who they hire post–product-market fit.
Instead of building large go-to-market and ops teams, founders are advised to hire more strong engineers who understand LLMs and can systematically automate growth bottlenecks and internal functions.
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Early LLM apps (simple text wrappers) are giving way to deep, workflow-level agents.
The shift from “ChatGPT wrappers” to agents that handle complex workflows—like enterprise support with thousands of test cases or high-stakes voice debt collection—shows the technology maturing into mission‑critical systems.
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Verticalization will likely precede eventual rebundling into broader platforms.
As in SaaS, the market may first fragment into many specialized agents; over time, some firms may expand horizontally (à la Rippling) by leveraging shared infra and large customer bases, but we’re still in the early, highly vertical phase.
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Notable Quotes
“Literally every company that is a SaaS unicorn, you could imagine there is a vertical AI unicorn equivalent in some new universe.”
— Jared
“The vertical AI equivalent is just gonna be the software plus the people in one product.”
— Jared
“If you can find a boring, repetitive admin task, there is likely going to be a billion‑dollar AI agent startup if you keep digging deep enough into it.”
— Harj
“These vertical AI agent companies can be ten times as big as the SaaS companies that they are disrupting.”
— Diana
“The rocks can talk and can have conversations, but the more interesting thing is that the rocks can read.”
— Garry (paraphrasing Parker Conrad)
Questions Answered in This Episode
In a world of vertical AI agents, what skills and roles remain most defensible for humans over the next decade?
The hosts argue that vertical AI agents—AI systems tailored to specific business functions—could produce at least 300 new billion‑dollar companies, potentially becoming 10x larger than today’s SaaS winners because they replace both software and headcount.
Get the full analysis with uListen AI
How should a founder evaluate whether a given administrative workflow is ready for full AI automation versus partial augmentation?
They draw historical parallels between the rise of SaaS (enabled by browser tech like XMLHttpRequest) and the current LLM wave, emphasizing that most value in the last era accrued to B2B vertical tools rather than obvious consumer apps.
Get the full analysis with uListen AI
What new risks—ethical, regulatory, or organizational—emerge when entire teams are replaced by agents rather than just supported by software?
Vertical AI agents are already gaining traction in domains like QA testing, recruiting, customer support, developer relations, call centers, surveys, and medical/dental billing by fully automating previously human‑heavy workflows.
Get the full analysis with uListen AI
Will horizontal platforms like Rippling or Salesforce eventually absorb many vertical AI agents, or will specialization remain structurally favored?
The conversation explores why incumbents rarely dominate vertical software, how AI may change company scaling and org design, and how founders should identify promising verticals by targeting boring, repetitive administrative work they understand deeply.
Get the full analysis with uListen AI
How might AI that can “think,” not just read and summarize, change the balance of power between executives, employees, and the AI systems themselves?
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Transcript Preview
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.
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.
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, Jared is a man on fire, and he's gonna talk about vertical AI.
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.
Nice.
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.
Software's pretty awesome.
Yep.
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?
(laughs) Oh my God.
Like I'd, I'd argue that that was quite literally the catalyst for the SaaS boom.
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