LIVE SaaStr AI Day: What's New with AI in SaaS with SaaStr, Synthesia and Theory Ventures

for 2025. We did this last year and with the goal of really doing a deep dive at the intersection of AI and B2B. And luckily for our kickoff today, we've got two folks joining us just to have a discussion on what's literally going on today. And I think it's some ways it's so— I can't even keep up. We'll talk a little bit about Deep— I can't even keep up after Deepseek and everything. It felt like a year ago was insane. We've got Victor Ripabelli from Synthesia. We'll talk, we'll first do a little bit of a deep dive there. Synthesia just raised a big round at $2.5 billion or something like that. I mean, you gotta keep, you gotta keep up with, with OpenAI and on the, I mean, that's, that's sort of like a seed round these days, but pretty impressive. We'll dig in a second, but I mean, Victor has been at the intersection of AI and B2B and enterprise doing AI-based video and training for enterprises. So no one's been thinking about the intersection of the two probably more. And Victor was with us in SaaS Europe in London last summer, and I'm gonna ask him what's changed. And obviously we all know Tomáš Tunges from now Theory Ventures. In the last 14 months, he's raised just only like $900 million or something across 2 funds in 14 months or something like that. Is that about right?

A little less than that, closer to $700, but—

Okay. Well, the pace has picked up for AI investors. It used to be that like $60 million was a lot for a first-time fund. $50 million. Now guys like to— now, granted, not a new investor, but a new fund can raise like approaching $1 billion in 24 months to invest in AI and data. I mean, honestly, it is a derivative of what's changing, isn't it?

But check sizes are up. I mean, lead check sizes are up 42% in 18 months.

Yeah. So I want to dig into that, but I can't think of anyone to talk about right now. The intersection, and I want to go into some of the data with Tomáš. But before we get there, Viktor, get us up to speed. So you've been doing— give me a deep dive on Synthesia and where it wins. But if roughly speaking, you've got hundreds of relatively larger customers using, using your AI training. Here's you yourself on the screen, right? You think using your own product. Doing in many cases nuts and bolts B2B activities, right? Corporate training, sales training, external on websites, internal SKOs, which we thought we wouldn't need any salespeople with, with AI. It turns out we need more than ever. But you're kind of at the intersection of an area that is competitive, right? There's a, I mean, there's more than one vendor doing video and enterprise, but you know, you're on one side or the other of 9-figure in revenue monetizing this. So get us up to speed on what you do today. And actually, what would be interesting to me is like, with all the change, what are you most excited about that you're gonna release this year?

Yeah, thanks for, for having me. So, I mean, today we, we're the largest AI video platform for the enterprise, right? And, you know, 4 years ago, that all kind of started with avatars. So most of those who are familiar with Synthesia probably think of Synthesia as being like the avatar company. We invented this technology where instead of recording yourself with a camera, You simply create an avatar of yourself or use one of our kind of off-the-shelf avatars. You type out something and boom, magically a video comes out, which obviously is 100 times more efficient than having to record yourself and gives you all the added benefits. You can go back and edit it after the fact. You can translate it into different languages and a whole bunch of other really cool things. And where we've gotten to today is that that is still for sure a very important headline feature of Synthesia. But really, we are an AI video platform today and we help our customers predominantly in enterprise. We also have a freemium model, self-service motion, but enterprise is what we're focusing on. On communicating better. And that could be with their, you know, employees, could be with customers, could be with partners. In 2024, people want to consume their content in video or audio format. They do not want to read anymore, right? It's a lot of text in enterprise.

It's true.

And so what we've been very successful at doing is building a video tool, right, which has avatars as a component, has AI voices as a component, has an AI screen recorder as a component. But everything is sort of put into this Canva PowerPoint style flow, right? And so the reason we're growing so fast is because what we essentially have done is we've enabled any white-collar office worker who knows how to make a PowerPoint to make a video, right? Before Synthesia, you'd have to go to the video production department with your idea. They would stack rank it against 10 other ideas. They'd say, no, Jason M. Lemkin, your idea is not important enough. We'll do what the market team wants to do. And you kind of have to go through all that stuff, right? If you did manage to get a video through and you're doing customer support, then, you know, one month after you've made 20 beautiful customer support videos, they're all out of date because you changed the product name, the policy is—

they're all out of date, is different, everything's out of date, right?

And that's a horrible thing to change. But with this new platform that we've built, right, you can just go back and edit it after the fact, which is incredibly powerful. And so I think what we've graduated from over the last 4 years, right, is being the training company with avatars, now being the enterprise video platform. That's what we're building. And the way we think of that is if you look at the video value chain, No one has ever managed to build a really, really big company about enterprise video. And we think the reason for that is that the value chain has been completely disjointed, right? You have a camera where you shoot some content with, you go to Adobe to edit it, you go to Frame.io to collaborate on it, you'd go to Vimeo to then publish that content, or maybe YouTube depending on what your goals are. And what we've done is actually we've collapsed all that into one platform, give you all the tools to make the videos, and it's so easy that anyone can do it. It's a full modern collaborative platform, right? It's a content management system where you can, you know, have teams and organizations and your CAO is happy because we have audit log, all the sort of stuff you need, right? It's, it's collaborative and you can translate, update the content. Then we also give you a publishing platform, which is a relatively new product for us, but essentially gives you a video player where you can deliver the content to your end users. And that's exciting because when we own that entire video value chain, we can this year begin to do a lot of things you couldn't do if we hadn't bundled it. For example, we can begin to use the engagement data of the videos to automatically create new versions of the video that perform better than the previous one. We can make your videos interactive, you know, bidirectional communication, which of course is— think of it as like AI agents, right? But you can— it's not just a video that goes, plays from A to B. It's kind of like an experience. It's like a small app almost you can interact with. So really what's exciting here is like, is the future of communication, which I think you look at people's private lives. Everybody listens to podcasts and watches TikTok videos and YouTube videos. But when we go to work in the buying process, in as a customer, right, when you're receiving support somewhere, all that stuff's text. We're helping customers, we're helping enterprise essentially uplevel their communications, which drives all sorts of different business outcomes depending on our customers.

So you're saying that folks that have blogged for a while, like Tomas and I, were just— it's dead. Like, there's like, we just, we should just, it's over.

It's the distant past.

Time to hang it up. Time to hang it up. There actually aren't many bloggers left.

Okay.

One quick question on this. And then we can dig in a little bit into today. And I want to— let's use your round in a second as a case study. Let's use it with Tomas. But what is some— with the latest models, latest everything, we can talk about DeepSeek for a moment in the next. What's something you're excited that you can do this year in an upcoming release that maybe you couldn't even do last year? What is something literally that's at the bleeding edge that you're doing for real in the enterprise?

So we're launching our new AI video models within the next like 3 to 6 months, and they're going to be a massive upgrade both in terms of quality and fidelity of the avatar. So those of you who've tried the product will probably have experienced the avatars are great. They're a lot better the last 12 to 18 months than they were, you know, previous to that. But there's still some way to go before it's completely photorealistic, right? We've got to pass through that barrier and we're also going to enable you to basically prompt your avatar into a new environment. So for example, you know, if you create an avatar of yourself today, you're kind of stuck wherever you recorded your avatar. In your office, for example. What you can do with this new tech is you can say, hey, put me in the jungle, put me in a supermarket, you know, put me like I'm playing tennis or something like that. That opens up an entirely new creative dimension in the product. And so those two things together have always been one of the core mechanisms of Synthesia, right? The better the quality of the avatars and voices, the more TAM we unlock. So a lot of people laughed at us 4 years ago for going after the training market. And because it's not a very sexy market, VCs hate learning and development, right?

Oh, well, I get it, but I get it. Didn't, maybe didn't sound like the hottest space, right? We get it. But a mid-sized market in all fairness, right? Even it's mid-sized, right? Classically.

I think more importantly than that, you know, you could get to, you know, double-digit AR just serving that market. And the thing that we, I think, saw that there's so many, you know, graveyard of competitors that have died around us over the last 8 years was that we focused on a use case where the technology was actually good enough, not where we could dream it to be one day, but to doing all sorts of cool marketing and sales content. It worked well for training because the alternative to training was a boring PDF document. And so what we've seen over the last couple of years, right, is that the better the avatar quality becomes, the bigger the TAM gets. So the last 12 to 18 months, we've seen a massive shift towards product marketing and customer support, which collectively those two are now actually the biggest segments that we serve. And that's purely because the quality of the avatars have gotten better and better. We're not making like, you know, we're not making Super Bowl ads and key brand moments, but we make a lot of tactical marketing content, right? So You, you know, you see the cool ad on, on Meta, YouTube, whatever, you click to the website, and then once you're on the website, then you learn more about the product with Synthesia videos. And we just gotta move further and further up that funnel, the better the quality of the advertising voice has become.

So the further you, you leave the uncanny valley, the customers can see it and you're seeing more market pull, right?

Exactly.

Yeah. Cool. All right. I wanna dig into that a little bit more, but, but, but before we do, just 'cause it, we, the agenda changed in a week. Deep, deep seek, right? I saw a lot of folks talking about this on social media and X. I don't know if you guys did. I want to get both of your opinions, but listen, I'm not— I'm the least smart person probably of all the folks that are watching. But I have an AI test and I want to know what you got. It's called the Sopranos test, and I've been running this for a while. Okay. I'm a basic guy, but I do enjoy writing in the word and I go in and I ask what happens after— Victor, you watch— you watch The Sopranos over there in Europe. Have you seen the show? Probably don't know. Well, anyhow, famous show in the United States. And it's crazy at the end of the— now, there is a rule, I think after 20 years, there's no spoilers, right? I think that's the rule on Reddit. Okay. So in the very end, the screen goes black. And people have debated this for 20 years, what happens in the last. And so I asked, I asked ChatGPT, and I asked, and I asked every— and I asked Claude, and I asked Deepsea, and Deepsea won. It's the best ending. It was the best ending, right? That doesn't mean that it gives me my best diagnosis for why my cholesterol's high or others, but that was my moment where it was pretty cool. So for this one use case, it seemed like instant parity. So first, Tomas, what's your take in general? And is this real? I mean, it's only been a couple days, right? Is this gonna make B2B apps an order of magnitude cheaper? What's the impact?

I think the impact is, I mean, your gross margins are so much better than they used to be, right? Like the second biggest cost for AI-enabled SaaS applications has been inference. And when we were looking, you know, like a typical software company is probably at 75% gross margin. A lot of these AI software application companies are like 0 to 30%. And now their single biggest cost has been reduced by 95% overnight and they didn't have to do a thing. So now they, now, now they have AI, you know, And you, Jason, you and I both know this, like the growth rates of AI companies are much faster than say the classic SaaS businesses just because there's so much in them. And so now you have companies that are growing 1 to 7 or, you know, some massive growth rate. Before they used to have challenging gross margins and now they'll probably look the same as SaaS companies, which means you have pretty significant multiple and valuation expansion.

Yeah.

So I think it's, I mean, at the application layer, this is like an unbelievable Christmas present that, that came on January 22nd.

Yeah. I want to share a story, but Victor, will this— is your COGS going to— is your COGS a huge issue and is it going to plummet? Or just from the perspective of Synthesia, is this not as big a deal as it sounds from COGS and the rest? What's your learnings in 48 hours?

I mean, we have great software margins already, so I wouldn't say it's not something we'd like put a lot of focus and emphasis towards. But obviously, as we scale up, right, it's great. I would say though, I think I totally agree with Thomas. It's a massive technical breakthrough. I think It's interesting when you look at the market. I think if anything, to me, this is just confirmation that humans and markets are driven by stories and emotions, not fundamentals, right? It's absolutely hilarious to see all the world's tech analysts who know nothing about AI just panicking because there's like a new model out. I think people have a tendency to overestimate the impact of this in the short term and maybe underestimate it in the long term. I think the long-term tail effects, as Thomas just said, for the application layer is huge, right? I think that's really massive. But I think in 2 months, I think 99.9% of the people who are using Anthropic and OpenAI today is going to go back to using their products, not Deepseek's model. And there's a big differentiation between those two, right? I tweeted the other day that smart people talk about models and benchmarks and customers talk about app flows, apps and workflows, right? And there's such a big difference of like a model that performs better and is interesting technically, right? They'll probably have a big again, long-term effect in the market. But, but, but, but yeah, I think there's kind of like the panic that's going on right now, I think is, is, is, is pretty funny. I don't think that most people who are using OpenAI and Froppy today is gonna switch over to Deepseek magically within the next couple of weeks.

I'll tell you just my, and again, I'm the least smart. I might, but my gut just from my little portfolio and little slice of the world is I think cost is less important in B2B in some cases. Than that you can use more. Because when I look at a couple of companies, one, one I invested in the contact center, which is all about AI agents called Gorgeous Free Commerce. They're at almost $100 million. Okay. At first, you know, the AI was $1 million a month, right, to deploy these agents. Now it's fine, right? They've optimized it. Right. And then I was a small investment at the low end of video in a company called Opus Pro, Opus Clip, that Victor probably knows. And when I invested, I'm like, this company's got to be burning I mean, you're uploading billions of videos and you're, you're creating clips for free. Like, this business model can't work, right? And I look and when I met— oh, it's actually cash flow positive, right? And it was wildly expensive, but as soon as they made huge commits and optimized what they're doing, and at the corner, maybe even, uh, cut a few corners— not literally, I mean, it's a great product, but maybe didn't have to do everything, right? They don't render all the videos in real time. They adapted So my thought is a lot of B2B folks I know, I don't think Salesforce's gross margins are going to plummet to 20% because of Agentforce, but we might be able to make these products in one year like 10 times better, right? Whether it's getting rid of the last bit of the candy valley or giving agents out for free. Like, you know, when I, you know, you guys probably know this, but when I, when I talk with Brian Halligan the other day, I didn't realize Dharmesh— I mean, right now HubSpot isn't charging for their agents, right? And this is a related point. I don't know what you think, Tomasz. I think what if, if everything gets better and cheaper, we just might not be able to justify $2 for a resolution. It might have to be included.

You think it'll be bundled because it's so inexpensive?

HubSpot's not sure they can charge. Marc Benioff is, but it's early. It's early. Customers aren't stupid. And I think we've all gotten ripped off the last 2.5 years with endless price increases, endless price increases. And I think another one. Now you're crappy. Like, if your agent's like mediocre, I ain't going to pay for it. I think it might be a VC fantasy, just like the fact— going to Victor's point— just like Deepseek has changed the world in 48 hours, it might be a VC fantasy that every B2B company can charge 50 to 70% more because of these additional per-resolution charges. I just don't know, but I actually think it might be deflationary in SaaS for the first time.

I think it's, it's, it's much more difficult for incumbents who are adding on AI functionalities that they need to charge for to not, you know, erode their margins essentially. Much easier for a startup who's built a product where it is the product, right? Because I think, I think ultimately you don't pay for like the models, right? You pay for the product. And I think it's just for Agentfall, for some of these big things, I think frankly, I'd also say a lot of them, I don't really, not sure they figured out exactly where this stuff is valuable. Like there's a lot of like, hey, we're doing like cool things and everyone agrees that it's cool, but does it actually impact your business? Whereas I think some of those smaller AI-native companies, I would put ourselves in that category, have actually found a very real problem. We deliver very, very real business value. And then, you know, it's kind of built into the— it's built into our business model already, right? But I definitely think it's like Copilot, right? Are you really going to pay a lot more for Copilot for all your employees? Like, clearly that seems to not be the case for a lot of big companies because they just can't pinpoint the value.

Yeah, I don't know. What do you think? I just don't— I'm just trying to learn in real time. I don't know. I just don't know in a year if everyone will be able to charge another 50% for enterprise applications for their AI add-ons and agents. They may be forced to, especially if the cost goes down another— I don't know exactly how the economics really work at Deepseek, but if it's really an order of magnitude cheaper, right? How long, how, how often can you charge $2 for, for what costs a fraction of a cent to deliver?

Yeah, I maybe, but like software's never been cost-based pricing, right? I mean, Twilio, okay, fine. They stack a margin on top of the SMS cost to the underlying—

Stripe.

Stripe, okay, but like—

A lot of APIs are cost-based, but keep going. I'm with you. I'm with you.

I mean, like Gainsight, you know, they're not marking up AWS storage, right? Or like compute. So I hear what you're saying. I think, but I do think the point that you made at the beginning, I completely agree with, which is like, if Deepseek-like models with great reasoning are 95% cheaper, Yeah, software companies will just like 10x or 100x the use and probably keep the margins the same to get to a much better user experience as a way of differentiation, right? So I think that the UX, our expectations as users for what these things are going to do are going to go way up because they become increasingly sophisticated. And like if you play with DeepSeek, I was trying to create a flowchart. I took the DeepSeek paper, the academic paper, and I put it in a DeepSeek and I said, create a flowchart for me of what they did. I think it was hard to read an academic paper. It spent 2 and a half minutes thinking, and I was watching it. At first it said, okay, but the user said create a single chart, but the experiments actually have 3 branches. So now I have to decide, like, do I create one single chart or do I create a chart with 3 different branches? And it like went back and forth, back and forth, back and forth. And now I understand, okay, well, next time I ask it to make a chart, I need to be clear on this point. Just the same way that we learned how to use Google, we're learning how to use these models. And this is one of the first models that narrates the way that it thinks. And I, I think that way we'll start to get to more outcomes. And then I think the other question that's really relevant to this conversation is, are we selling outcomes now in software as opposed to selling seats?

Yeah.

And I don't know the answer, like, but the mantra has been we're selling outcomes, we're selling outcomes, we're selling leads, not, um, not SDR seats, we're selling, uh, resolved customer support cases or videos or, or clicks. And if, if that we do get to that place, then I think it doesn't matter how cheap these things become because there's some break even for a customer to use the AI rather than—

Yes. My limited, you know, it's funny. I, I dug up, I have a post coming out up in my queue, but I dug up, I went back through a bunch of those old KeyBank SaaS studies, right? Yeah. And it turns out going back to the beginning, per seat was less than 50% of SaaS revenue. What? Yeah. When you add in API pricing, other pricing, just because we think everyone talks about blah, blah, blah Salesforce, it doesn't mean it's most of software, right? And so it's, it was like 47% in like 2020 or 2021. Okay. So I'm not saying it won't continue to decline, but VC shooting from the hip on social media is saying the seat is dead. The seat was never, was, was at best a plurality of revenue. And, but I wonder, I have just one investment I've made where the customer was playing in kind of a hybrid model. Right. And listen, this is not like the most profound insight, but it crossed $1 million that they were paying very quickly. And of course, what happened the next day? Oh, hey, hey, Victor, we love Cynthia, but $1 billion a week, we need a flat rate.

You like—

no more of this. Like, variable cost, it destroys the enterprise. No enterprise, no matter what. And maybe you guys both have insights. Enterprises still want visibility. There is the ability to move some budget around. There is ability to take budget a piece, but everyone wants certainty, right? If everyone wants, everyone's, everyone wants Snowflake as much as they can in their Snowflake spend. They want Snowflake here, right? So I don't know if this is as radical as the internet wants it to be. How do your customers want to pay, Victor? Do they want to, do they want to pay in brand new ways or do they want to pay in the same way their grandfather paid for business software?

I mean, we still sell seats predominantly, and I think, I think it depends just a lot on the product, right? I think the way to think about Synthesia right now is PowerPoint 2.0, right? And like PowerPoint is one of those things where like, you know, we have thousands of people using this inside, you know, big enterprises. And I think that's, that's like, that's, that's easy to understand why we're selling seats. I think, you know, we also want to sell outcomes. You know, we are building kind of more specific workflows that solve like, you know, reducing, deflecting customer support calls to the call center or increasing the efficiency of sales prospecting, which we kind of like build separately. But I think it just, I think it really just depends a lot on the product, right? If it's, I think there's probably a lot of companies who kind of over-indexed on seats where it doesn't really make sense. In a creator tool, I think seats make sense, right? But a whole bunch of other types of tools where seats maybe isn't like the right isn't driving down to.

Yeah, I don't know. Let— I wanna move on to fundraising. I just— my only thought is for founders and others, I just think— just got it. You just— I would just be a little cautious on social media think because I don't think most business customers want pricing that is radically different than their last product. Right? If I paid this much, if I'm paying $300 for a month for Salesforce and I'm moving to, to this new version, like, $200 seems cheap, but you want $0.83 per contact resolution. I, I mean, it's just, it's, that may add friction to the sales process, right? And there are certain ways, and if I'm, I think of everyone that's like Stripe-esque prices, Stripe-esque that I've seen, right? Um, and we may, if you're, if, and I think we may be playing, spending too many mental calories and playing too many games on pricing when we should focus more on closing customers in a low friction manner, right? I think this is over, overdone, this issue, right?

I think the deeper insight here, which I have confirmed so many times over the last years, is just to not over-index on social media, I think, right? Like of what VCs want or like what I want as a founder. It's like, just talk to your customers, listen to what they want, help them deliver awesome value and the rest will take care of itself, right? Yeah, it's a bit like, I think with all this like model stuff, it's like most customers don't really care about models, right? They buy products. And I think in the tech world, we love talking about technologies and whatever. It's like 8G, latest like hype cycle. But when the rubber hits the road, eventually you can't just live on like buzzwords and, you know, kind of grand ideas. Yeah, I think that that's always— that's a big lesson for me the last 8 years for sure.

Okay. I want to spend just a couple of minutes on overall VC fundraising because I have both of you right. Victor's been at this since 2017 before the buzzwords were cool, just raised What I think is a real round, right? $2.3 billion or whatever it was. That sounds like a lot, but you're not at $2.3 million in ARR, right? I mean, you haven't disclosed. I won't ask you, but you're on one side or the other of 9 figures in revenue. Like, I think they got a good deal, but okay. So I want to ask—

best risk reward.

Great deal. Great. Seriously. So Tomas, I stole this chart from E&Y, which stole half their data from Crunchbase. Which probably got it all out of Deepseek and OpenAI anyway. So we're all stealing each other's data, but this isn't mine. But I like this version of what we've seen before, even though— which is what happened at the end of last year is money went way up, right? As we can see on the left, which we all saw on at least on TechCrunch, right? But deals didn't. Deals went down, right? A lot of it was growth-focused and half of it was AI-focused. But this says to me, if you're, if you're in the hot zone of Synthesia and we, Victor, in a minute you can tell us what hot is. It's, it's, it's the good, it's as good as almost as good as 2021, right? Maybe it will be better, I think this year, but overall deals are down. Is this what you're seeing? And so does this mean we're in a real world where the folks that are saying fundraising's harder are right? And the folks that are saying it's froth are right? Is everybody right?

I think everybody's right. I mean, you look at Databricks raising $15 billion.

Yeah.

You know, I mean, that's as big as the Facebook IPO was, which was the largest technology IPO at the time in 2014 or 2015, whenever it was. And they did that in the private markets, right?

Yeah.

OpenAI raising $5 billion. So there's, you know, you have $20 billion, let's say, of that $60 billion in Q4 going to 2 companies, a third of the dollars. And so it's really like what you're seeing here is The early-stage deal counts, I think, you know, probably the same. The growth-stage deal counts are down in a pretty meaningful way. After 2022, the Series B through the D market was effectively dead, and it's starting to come back. But, you know, if you're— if your check sizes are measured in the billions now to lead to financing, you can't invest in many companies.

So for— and what's your pulse for your average? And even this is top 1%, right? Or even higher. But what's your pulse for, for the classic B2B triple, triple, double, double company, which was what everyone wanted to fund in 2021? What's your pulse on that in 2025?

I think it's a, it's like a lower multiple A. I think it's like a very reasonably priced investment.

But the deal gets done. But they all get done. All the triple, triple, double doubles get done.

No, I don't. Not even. I mean, maybe on the margin, kind of depending on the valuation. And depending on the market. I think the hard part is those triple, triple doubles in classic software. There's a lot more competition than there once was. Now all of a sudden you look at a company in a particular space and the last 10 years, you know, you and I have funded a lot of those companies and many of our friends have funded those companies. And so like if you're tripling, tripling, doubling, doubling without AI, it's, it's a hard sell.

And then that's the thing with AI, like you used to have 2 competitors, now you have 400. I can't even keep track. Like I can't even meet with a startup that's like pre-seed, whatever, because there's like 4. How many, how many other AI legal, uh, in-house litigators could there be? Like, this was the most boring category when I invested in legal in 2015. Now there's 1,000 startups, right?

Kind of the Groupon era for B2B. Remember that era of Groupon where like Groupon came out and then there were 1,000 Chinese competitors within like 6 weeks? Yeah, or a few hundred in the US. It's kind of the Groupon era for AI where one company takes off and then there are 15 to 20 others because you're, you're wrapping the API, you have a lot of capability out of the gate, and then long-term product differentiation probably matters less than go-to-market execution.

Yeah, the products are superficially great now, right? Versus they used to— all our products in the old days, the first 18 months, were terrible. Like, they had one cool thing, they did one cool thing, everything else was terrible. Now these products, at least superficially— like, you, you talk about AI agents, how, you know, people can't get ROI from them, but superficially all— I mean, the AI SDR, superficially all the products are great. Like in a quick drive-by, every AI SDR product's great, isn't it?

The demo's amazing.

Demo's amazing.

Demo's amazing.

Demo's amazing. All right, Victor, what did you— on this slide, was this the easiest round to raise?

It wasn't the easiest round to raise. I think, I mean, at the valuations that we are in now, right?

Yeah.

It's, it's— and especially when you have a really good business, which I think we do, like not just from like a Amazing vision, great story, but actually numbers, customers, expand their contracts. Like the more, the more data and numbers you have, the more you will get evaluated in those things, right? So I think there's like, there's these like very outlier deals where you're like Devin AI or something and you're like, he's like 6 engineers is absolutely insane and they're going to change the entire world of coding. It's like boom, $2 billion valuation. You can do that maybe if you have like a really strong story and there's like a team and whatever. But I think those are still pretty outlier. My sense from like also speaking to peers is that when you're raising growth rounds now. And, you know, we're not a foundation model company. We're very applied. We're definitely evaluated like a SaaS company, definitely with some premium because we're kind of, you know, very AI native. But I think it's a fair price. I think it's a good investment. I think the risk reward in this round is the best it's ever been. I think we raised Series C, you know, that was kind of coming out a lot of like hype cycle. You know, ChatGPT had just dropped. Everyone was like freaking out and we were growing super fast and we were closing a lot of, of, of, of contracts. Right. But it was still to be determined, like, can we get to million-dollar contracts? Will people actually get consistent value out of this? Are they just trying it out? Is it innovation budgets? All of those questions were still kind of open. But I think we raised this round. What, what I think stood out to the market here was that not only are we good at closing new logos and closing new business, but we are very good at the renewals and the expansion, right? And ultimately, that's where your customers vote if your product is just a cool demo, of which there's a lot right now, or is it actually something that derives real business value? And my sense from, from spending time with a lot of investors, right, is that a lot of— there's a bit of fatigue of like, okay, great, you grew really quickly, you closed a lot of contracts. And but that doesn't necessarily mean that that translates into lasting value. There's this— I think there's this weird thing in AI right now where it's very fear-driven and people are very willing to part ways with their money, both on consumer side but also in businesses, to try out new things, right? Because everyone is like scared that their business is going to, you know, completely disappear because OpenAI is going to kill them next month. They're afraid to lose their job if they don't have an AI strategy, if they don't appear to be an AI expert. In reality, I think most enterprise buyers don't really know what they need. They don't really understand the technologies that they try out, lots of different things, which may be a sound tactic, right? But it means that there's a lot of like this demo budget that's kind of sloshing around. Yeah. And I think that's one of the things that stood out to investors in this round.

Well, it's interesting how important durable revenue was for the round, right? That it's durable. Is that, Thomas, that's another thing on the, on the VC social media. Are folks still anxious that so much of this revenue is discretionary, that it's experiment, that it won't stick, that it's non-durable to Victor's point, or is that fading as a concern?

I, well, I still think, I still think it's a concern. It's probably not as much of a concern as it was last year. Last year, buyer preferences were changing so fast. I mean, the underlying architectures were changing, the models were changing in a really meaningful way. You know, are we doing keyword search? Are we doing RAG, different kinds of databases? We're trying to figure it out. And as preferences change, you had whole categories come and go within the span of a year or 18 months. I don't think we're, we're quite there yet. I think where we are, particularly at the application layer, is trying to figure out which AI agents actually produce value.

Like, yeah.

How much am I willing to pay for a note-taker? Right? Leslie's note-taker just joined the waiting room. I, I wonder how much paying for? Is like $5, $10?

How many do we need? 100 note-taker apps?

What's your sense?

Actually, you know, a friend of mine tweeted, he said this is the— he attended a meeting this week where there were more robots than there were humans, and one person didn't attend and just sent their note-taker.

And I don't know if you've done this, but like sometimes I want to listen to webinar, but like, look at this call, look at this call, there's at least like 20, 30 note-takers. Just—

yeah, tries to boot them, but they keep coming.

Yeah.

And then you— so, you know, you can attend a meeting virtually, I mean, whatever, bionically, so to speak.

Yeah.

So I think the question is like, okay, how much are you willing to pay for that? Will Zoom bundle it in? Will Google Meet bundle it in? And so is there price erosion there? Um, and so maybe that kind of creates churn, but I don't think there's sort of this like category cataclysm that maybe we saw in '24.

Yeah. All right, well, let me tie this to the last point I want to give on, and then if we have time, we can take some questions. So folks, I don't know, folks have put questions, or they can put questions in the chat. We'll try to do that with our last minutes. But this ties to like a meta question I have. So one of the questions last year was is this all experimentation budget? Will it fade away? Is it durable? To Victor's point, right? Victor had to prove that he has triple-digit NRR and all the things. Eventually all these companies have to converge to real software companies, probably IPO and everything, right? Then where I'm really getting confused is on agents. I'm not confused about the hype and what they can do and whether our agents can all talk to our agents and our agents' agents. That's going to be— I think it's exciting, right? I'm just wondering how many of these we can pay for, how many of these can— and I just looked this morning, you know, Dharmesh from HubSpot has a little AI agent. He's got a bunch of things on his network, but he's got a little marketplace, which I'm sure in 6 months will be an order of magnitude larger. Right. He's got 629 agents right here. Salesforce charging $2. But this was— there was one on the bottom right is the latest data from Zylo, and they're all fairly consistent. Which is basically over the last year people didn't add any NetApps. They didn't add any NetApps to their stack, right? Whether that means they're actually adding some but consolidating on their core apps, right? I think, you know, I should have known this, but Victor, you can do it. I think Synthesia is a swap, right? It's going to be a swap in some cases, right? You're going to swap. It's not a total always a new app. You may be swapping out a training app. You may be swapping out part of the Adobe empire as you go, right? It may not. But, but how many can we— I believe that the, all the energy in venture, in startups, in YC, in SF is somehow based on this idea we're gonna pay for like 3 to 4 times more agents. And so we're gonna like triple or quadruple our app stack. Can we, is it true? Can, and can we process this many paid agents? Or is this all a, a big VC hype cycle that's gonna implode because we can't pay for 500 of these agents? What do you, what do you think first, Tomas? Is this, does, does my question make sense? Is where I'm confused.

So I think, um, I think we see, I mean, we're seeing consolidation across the SaaS stack where you just have bundling everywhere. Like you look at the sales stack, you see mass consolidation across SDR automation. So I, I, I think you'll see a reduction there. I think people will end up buying agents for different reasons than they bought classic software. Like for example, um, we're investor, like if you're a large enterprise, you have 641 apps. You probably have some pretty significant security apparatus. You have another 75 security products. Those produce 8,000 alerts. Less than 1% of those alerts are reviewed by humans. Now, it's a law that you have to review all of them. People aren't gonna buy additional, like, 5 other pieces of software. They'll probably buy, like, 100 agents. And those agents will do the job of the humans.

They're gonna pay for each agent $10 or $20 a month, and they're gonna manage them individually. The IT team or whoever is gonna have a whole nother set of 200 or 300 agents they have to manage.

Yeah, I think, well, I, you know, I'm not saying you're wrong.

I'm just trying to learn actually. Yeah, yeah.

No, I think that's right. I mean, you think about like the BDR of the future, right? BDR today manages one Gmail inbox with max 40 outbound emails. Maybe they manage 2 or 3. BDR of the future will be managing 40 or 50 Gmail inboxes. Yeah. And so, um, you know, the, I think like if you think about like there's a deflation in the number of seats because now all of a sudden BDR acceleration, well, I don't need nearly as many BDRs. but the value per seat goes up in a pretty meaningful way. And so I think maybe what we see is application count stays flat or maybe even decreases, but the total amount of software spend increases because it's capturing some fraction of that labor spend.

But are— so that, that's a— I, I get that and I can't predict the future, but aren't— if you just think about it from an old-fashioned enterprise, gotta manage X vendors, gotta manage rogue renewals, rogue increases, Like, do I really want an explosion of 5 times as many apps? Whether you call them agents, they're still apps from a procurement IT process, aren't they? Yeah. Still another goddamn thing I got to evaluate, do a security audit, do a cost-benefit analysis, make sure it doesn't go rogue. Like everyone went rogue in 2021 and bought 50 sales apps, right? I just feel that the cognitive load is high. The cost, not for the end user, but for the buyer.

Yeah, I, I think the successful software applications, like, whatever, as a salesperson, I might have 500 agents, each of which is managing one lead.

Yeah, you could.

Right? And, and so what is that agent doing? It's gathering the news and the social media and the podcast and transcribing it. And that's pretty easy to review. I just go through my list, like, what's the latest with Databricks? What's the latest with Snowflake? And each one of those is an agent. So I don't think the cognitive overhead is huge if the UX is correct.

But who pays for it? That I don't think for the— I think the bionic— I call it the mech AE, but the bionic SDR, I believe, is happening fast. Right. But who's— I've never found a single AE on all of planet Earth or even our galaxy who will put anything on their own credit card. I've never found an AE. So the company has to pay. I've never found a single sales rep, maybe in McMurdoch Station, that will pay for their own sales. But they won't. They got some. So who's going to pay for their agents if they're discrete, if they're not bundled into another, another app? Right. If they're not part of a platform, who's going to pay?

I think it comes from the sales. I mean, you've seen the sales budget. I don't know, 10 years ago, what was the sales budget per AE? Maybe $250, $300. Today?

Exactly. I think. Yeah. Right.

And so, and then 2022, what do you think it was? $750, $800, maybe $1,000. Yeah.

It doubled.

Yeah. And so Salesforce is half of that with Einstein, right? It's 175 base sales seat, put $500 to get with Einstein. And so I think you see some, you know, you see consolidation compression within the existing sales stack and some of that budget shifts to AI.

Okay. I don't know. I want to— I, I, you, you think about this much more than I do. This is just a meta worry for me is that no one's gonna— enterprises are gonna be fatigued reviewing 200 paid agents. Not if they're part of my stack, not if they're part of Synthesia for, for content creation, not if they're part of HubSpot. But 200 new vendors is exhausting. What my limited experience, both with my portfolio as a CEO and my brief experience in a big enterprise is there's there's just, there's only so many vendors you can bring in. And there are moments of time like 2020 when the world ended, right? And there are moments in time and there are always experimentation budgets if it's isolated, right? If it's isolated from risk. But when there's risk, I just worry there's that, that, um, we're not thinking through how we're gonna get these through the CIO's budget, right? Yeah. The CIO's budget. And I also don't think SMBs wanna pay for 100 agents on their own. I see SMBs being cheaper than ever today. They're cheaper than ever, right? They— the SMEs do not want 200 recurring things on their personal credit card.

But why do we— I don't understand this agents talk. Can someone clarify? Is this like just features that we're now calling agents, or is it platforms? Or like, I don't think that we'll think of like, well, we have like 200 agents like researching social media on behalf of our customers. Like, you'll have a— you buy a product that does that for you. Maybe it's part of your existing stack.

Well, maybe that's the question I'm asking you too. I think if I'm on— if I'm on Dharmesh's agent network, I think it's something we made up. Yeah, I'm— there's 629. I'm going to find— I'm going to deploy 100 of them.

I don't know. I just think it's such a weird— it's a weird way to talk about software and features. Like, I understand it's like— it's—

well, you're at the cutting edge. You're supposed to tell us this is what's happening. You're the funny daddy on that.

You know, I got here for real. I got here by not listening to the buzzwords, you know, and just like doing a great product that people love. I'm just trying to learn. It just weirds me out, all the stuff. It's like, it's features, man. It's like, it's an LLM-driven feature that does something for you. Why are we like trying to anthropomorphize it to be like an agent? Like, I understand like it sells to the marketplace and it's like, it's cool. And in some instances, maybe I can understand why we call it an agent. But I think majority of this is just weird. I think in 5 years' time, like, I think everyone's like, why the fuck did we spend 5 years talking about like algorithms as being like a coworker? It's just like software that does things for us. And sometimes maybe you want to chat with it. That's great. That's a new interface. But I really don't understand this, like, obsession with agents. And that said, you know, we're probably launching an AI agent strategy soon because everybody likes to talk about this stuff, right? Nobody wants to talk about features. So I get it from, like, a go-to-market and sales perspective. But it strikes me as well.

But it'll be part of your platform. You have thousands of customers.

So I don't have to— That's, like, weird to me, at least.

No, no. And then, Emilia, I don't know if we have any questions to take, or I could wrap up with the last minute. I don't have the answers. I'm challenging it. I just, I just, I think, to my points, right in 20— in second half of 2020 to 2021, somehow we magically found budget for all these new apps. Right. And the pandemic did it. Right. I mean, and if you saw it, like, I mean, the craziest one in my portfolio was Talkdesk, which is call center, like, and forget about how AI changed in 2020. You couldn't go to the office for the call center. Right. So everyone in their space and like they grew 5x in 6 months because IT changed the rules. Right? The IT changed the rules. And I think there are some rule changing happening, but I don't think in 2026 IT can double. I just think an agent counts as an app potentially if it's a vendor. Let me put it that maybe I'm, I'm rambling too much. Every new vendor in the enterprise's cognitive load, a new vendor to put into the procurement system to get approved, to track. And every, and every enterprise knows that if I bring in one, I, it's not just 1 year for Synthesia. Now I'm stuck for 8 years. Like, that's how enterprises think. They don't think one year. They're like, okay, it's gonna take me the first year I'm learning, the second year I'm rolling it out more, the third year I'm gonna buy more stuff. And they always like double— we, back at Adobe, like when you put any vendor in the system, you doubled the budget because you knew it was gonna grow with add-ons and seats. Right? And it was, and so how many of those can you add each year? Even at Adobe size, you just run out of vendors you can ma— and I don't know if AI change, if agents change that rule. They're gonna change a lot of other rules. And so I don't know who's gonna pay for that. I just don't know who's gonna pay for the discrete vendors, not the agents themselves, but so many vendors. So many vendors.

I do think they're like, they are fundamentally new product categories though. I would put us in one of like, we're never going to replace someone or take budget from someone. We probably will over time.

You don't come from the training budget or the LMS budget if you're for an internal, for an internal use case?

No, we'll, we'll sometimes take some of the video production budget that they'll go that use with agencies.

Yeah.

Um, but they, the, the key point here is that people not evaluating us against, should we, should we switch out this thing with something easier? Right. It's a net new thing. It's also why we're growing so fast. And I think there are new product categories like that. And then there'll be a lot of these agents or features or whatever that'll exist better within, you know, the platforms people already use. And, you know, they'll be kind of add-ons and extra modules, I think.

But I believe you that you— listen, you know, you're in all the deals. I believe you that you're not directly stealing someone's creaky old budget. But what I— my limited experience tells me behind the scenes, you're stealing someone else's budget. They're canceling someone that they don't quite need that was on the bubble. And they, this is, I mean, I, I don't think this has changed since I worked at a Fortune 500 tech company. You get together each year. Okay. This is why budget's annually. And Tomas, you wanna add that cool product, what are you gonna cut? This is why so many things got cut the last couple years.

Maybe some of the budget, maybe some of the budget does not come from software, right? It comes from like services-based things. So far in our case, a lot of the budget we eat into is like video production agencies, right? That's not software vendors. Or it's translation budgets, or it's kind of like more service-driven things. And I think especially if we talk about agents, right, that, that, that would probably be a lot of what that can lead into. So it's like you may add another software vendor, but maybe the budget doesn't come from like other software platforms, but it, but it comes from like services.

That's a lot of the hope on X is that we can turn humans into software budget, right?

Morgan Stanley ran a study in Q3, I think, and they said 50% of the AI budget was, uh, cannibalizing existing software and 50% was new.

50/50. That's probably right. Right. I mean, they got the data, right?

Yeah. And so I bet Victor is right. Like, it's translation or other kinds of services, consulting, customization, legal, like all that stuff, like legal outsourcing. That's where the software budget's coming from. It's eating away at the labor cost.

Yeah. So that's interesting. So you think— and then, Amelia, do we have any good questions or should we— I know, I know we've gone long. We might have lost— You do. You have a lot of comments, but we also have another session in like 2 minutes. Okay. We might have to wrap up and— and do them later. That is the 50/50. So the answer, like a lot of these things, is yes-ish, right? It's both, right? We are, and we're— and Tomas, just maybe to wrap it up, if so, 50% is cannibalization. Maybe Victor doesn't see it, but they're cutting videographer, they're cutting something else, right? The 50% that's net new budget, where's like the fortune? Like the GDP is still somewhat fixed in the United States. What's it growing? 3% a year, even under our new regime. So for real, where's the money coming from to, to bet? Where, where, where do they get, where does Morgan Stanley or Theory Ventures say, where are we getting this money and how long will it last?

I think it's labor. I mean, I'm seeing it in our portfolio, right? Like I look, I look at R&D spend and like year over year R&D growth compared to 10 years ago. We have one company growing really fast. Engineering headcount year over year will be flat.

Yeah.

Because they deploy some AI-enabled IDE and they can write a lot more software. And so instead of hiring another, say, 10 software engineers at $250,000, $300,000 a year, $3 million in spend, they're starting to spend, I don't know, $100,000 a year on AI software.

Do you think that's true from what you see, Victor? Do you, do you think we can do more with fewer engineers with AI and the new world? Or, or is that a, a bit of a, a bit of a myth?

No, I think we can, but I think, I think there'll be many different shapes of companies. I don't think there'll be one type of company where you really wanna go for it. I still think if you want to build a $100 billion company, you're going to need a lot of salespeople, you're going to need a lot of engineers. But I think there's no doubt that productivity is going through the roof. And it feels like we are seeing a lot of these types of companies, as Thomas is saying, right, where you can— and also it feels like the mindset has changed a little bit, but there's kind of a reluctance to like hiring more people and like just being more efficient, which I think is super awesome, right? But, but yeah, I think it's never black and white, right? But I think there's a, there's a definite new type of company. Which I think is super cool. But if you want to like tackle the enterprise like we are, I mean, that's, that's still very difficult to do without like adding significant headcount.

Yeah, you might even, I mean, if we were on VC Twitter, the way to take it to the extreme is the new vanity metric is ARR per employee, right?

Like, well, ARR per engineer is more interesting than ARR per employee. I could tell you why it's more interesting per engineer, per developer.

And that's like the sexiest metric. It's like, I think it's kind of one of the coolest. We're 10 people and we're generating $20 million in revenue. Like, Those kinds of ratios we wouldn't have seen.

Yeah.

A decade ago. And now, you know, people are striving for it and we hear it from founders. Like we, you know, we only have this many people. We don't wanna hire people. We're raising capital, but we're not hiring. That's unusual. That's, that's a very different, um, pitch.

Do you think I'm making this number up? But I think it's about right. And, and Victor could probably for in a case study and then when maybe we can break that makes it, that's what I see too. Right. My, my, and listen, the world's changing so quickly today. Right. I even did the whole deep sea thing. It feels like everything's faster than it was a week ago. But it feels to me there's still the issue around 200, 300 employees where you still end up needing 10 people to do everything. And what I feel like this 10 people can get to $10 million ARR thing, it just shifts the time. Like instead of me needing— but it's still at $100 million, at $50 million ARR, I need so many humans and honestly so many mediocre humans. You start having to hire. Okay, maybe that's the wrong term. You start after hiring A-minus tier and B-tier, no matter— even though you can't say it out loud. And it just takes so many people to do some of the basic stuff and you need so many salespeople and so many mediocre renewals people. And I just see everything still gumming up today at that size. Maybe if AI gets rid of that roadblock, that'd be awesome. But I wonder if it just shifts, kicks the can down the road a year or two.

Yeah, I mean, it's kind of like Salesforce hiring 1,000 salespeople to sell their SDR salespeople, right? The agents. I think there's still a lag. Like, I think we'll— I think it'll be definitely more efficient. But I still think that we're far from you being able to, you know, like, at least when you create like true enterprise software, I do think that's a bit different than, than like more consumer or like SMBs, like where you don't need the human touch. But it still feels difficult to close. It'd be very interesting if a company with like 20,000 employees, whatever, gets to close like million-dollar deals with enterprise. I think that would be like a really interesting kind of tipping point. But so far for most of the ones that I've seen, at least it's still a lot of like, you know, self-service credit card revenue or like, you know, kind of smaller sales because it's still just very difficult managing a deal desk, right? It's like you just need people for that.

Well, maybe let me just wrap. Let me ask one last version of this to you, Tomasz, then we could wrap. And this was great. So when we start, when you and I started, Tomasz, a lot of VCs would yell at founders and say, you've got to offshore to save money. You've got to everything till the magic solution. When we started, maybe you too, Victor, the magic solution with VCs was have 50 or 60% of your indie offshore that would magically cut your costs, right? Magically, because developers are fungible, they're all the same. So just hire a bunch of folks in some country you've never personally visited. And that's my VC solution. Is the new version today— the version of today is if you're good at AI, you only need 10 developers. It almost feels like it's the new version of offshore, is AI is the new offshore. Like you, you got— you— why do you need more than 10 guys?

I love that. I love that analogy.

Yeah, that's a great, that's a great, that's Tomorrow's blog post for you, I hope, Jason. I think like some people did offshoring really well. They hired a great country manager. They really spent the time to transfer the culture.

Some, yeah. Yeah.

The cost efficiencies. And then some people basically just, you know, mailed it in and you kind of got what you paid for. I think it's the same with AI. If you change your recruitment processes and you look for people who really understand how to prompt these systems really well and think about building with AI, I think you can drive a ton of efficiency. I think if your CEO has been told by VCs, hey, go employ AI within your engineering team and you buy a bunch of people some subscriptions.

Yeah, Cursor is the answer.

It's not. You have to change the way that you work and change the way the teams work. And that's really hard.

I also really still think that what I see across, like, no matter like what task we're talking about, where AI really shines is still augmenting humans, right? Like, In the case of us, we augment people to like make, make videos. Cursor works so well because it kind of puts the human in the driving seat and just makes you more efficient. I think there's like pipe dream of agents like just doing things completely autonomously, in my view, is still, still a while away.

Yeah, we'll see. We can break my limited experiences that an S-tier agent is better than a C-tier employee. This is what you see across the contact center is you usually see that the agents are like in the— they can't do everything, but they're in the top 10% of CSAT because what they do, they get done without complaining and they don't argue, but they can't be below. I think the whole world's going to that. Agents will replace the C tier like very quickly and deepen the B tier as they can. Right. And I don't know. All right, guys, this was great. We ran out of time. Victor, so great to have you back. We'll see you in London again. And Tomas, we'll see you at the next one, my friend. Thank you.

Thanks.

Thanks, guys.

Thanks, guys. We'll see you for the next session.

It's in the chat if you want to see us there.

Thanks for joining AI Day.