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“Well, I think open source models are going to dominate AI inferencing. You know, you'll see in the next two years, we'll shift to where's almost no open source to where's going to be almost all open source.”

“I think the model business, you know, on its own is, is actually probably not as lucrative as everybody believes, but these companies now have a lot more things.”

“I think it's a wrong goal in my opinion to say that, hey, like replace yourself with AI. First of all, I think you're giving too much credit to AI in, you know, when you say that. It's just not ready right now. There's, you give me a name of one job that you c…”

“If you were trying to do the same amount of work and you believe you can do it with fewer people and therefore you shrink your competition can also do the same, but they chose actually not to do the same amount of work. They chose to actually, you know, elevat…”

“And the, I don't think the world's greatest companies are going to be companies with a hundred people”

“I would say in, in the last 25 years that I've seen, I would say it's been, it's easier to build a startup And get a good exit from it these days than it used to be in the past.”

“In the future, all of that institutional learning is actually going to accumulate in that agent that is doing that work.”

“If you don't have any control on running that agent yourself, if you don't own the learning that it actually that actually, like, you know, gains over the years, then you're basically fully dependent on these AI companies, you know, to do, you know, to get you…”

“That's something that's happening now. So I think we are at a real inflection point with open source.”

“I think right now the open source drive is coming from the cost point of view.”

“When AI just came, there was a, companies were a lot more afraid of getting their data outside of, you know, their own control and model companies training with, you know, with their data. But that sort of is a fear that it's no longer there. Like, you know, l…”

“They are launching these sort of vertical packs, but I think they're quite quite shallow in my opinion.”

“We actually get a lot of credit for being the first enterprise AI company in the world. The first ones to actually bring RAG into the enterprise. The first ones to build conceptual semantic search.”

“From a point of view of open source and using the model, everybody's going to be fine. The question is going to be, are they okay with the Chinese model or not? That's the only question here. It's not open source versus closed source.”

“Well, we've been telling customers, I believe that majority, majority of enterprise workloads will actually be on open source models in three years for sure.”

“The actual shipping speed of products has not increased, even though coding, you know, increased, coding speed increased significantly.”

“I think the, you want to be performing the best in whatever you do. And I don't think you're going to take a 90% solution. Well, I mean, like, look, the they're kind of like, you know, like, it's a, it's not about you not being cost-constrained. It's about you…”

“Well, hopefully, you know, 5000. We're gonna grow.”

“But I also know that already you see with open source that you can do the same amount of same work for a 10th of the cost, right?”

“We are absolutely in a land grab, like, you know, no question. Like every single company in the world wants a product like ours today. And either we get in today or it's going to be like 10 times harder to actually get in the future.”

“A lot of analyst roles, like, or like the data analyst roles, which are not business thinkers, you know, they were given a task that, hey, like, I need to see this data, and then they produced, like, they sort of go and build those specific dashboards, configu…”

“I actually do think that, you know, there is too much capital available today in the for startups. And it's actually sometimes creating failure paths for people. I think they're not getting what it takes to build a great company.”

“I would say it's absurdly expensive. I'll give you an example. We had this, we have a really cool triage agent for engineering. You know, and we have 15 people team on call team that was supposed to, that their work was to actually triage Every single producti…”

“I actually do think that, you know, there is too much capital available today in the for startups. I like, I'll give you an example, like a startup that has raised a seed round, decides to pay half a million dollars to an engineer, like you were saying before …”

“The thing that I feel you know, is happening in enterprises, you hear these 95% of projects fail, But, like, you know, like, that's actually what you want. Like, you, like, when you are actually experimenting with new technology, if all of your projects are fa…”

“Going to grab a lot of revenue that actually today is in services industry, which is 25 times larger than software industry. So this is, there's a lot of spend that is going to move. I mean, the spend that you see happen on AI is actually sort of, you know, th…”

“So I think ultimately, like, software is an end-to-end stack in my opinion, and all of these companies, you know, I don't think they're going away. I don't think, you know, they're going to relegate it to becoming a database.”

“I want to see more proactive, proactive AI products coming, coming into the market next year. That, that's what, that, that is what is going to actually take it from a five percent of the users being power users to a hundred percent.”

“There's a lot of focus on embeddings and vector search over the last few years, but that's actually only one part of, ah, building a good search system. Because if you think about an enterprise, ah, imagine a company that has been around for a few decades. You…”

“I mean, I think there's always this thought of that, like, you know, the models will have near infinite context windows and you can just give them everything and they can figure things out automatically. But I don't think, you know, like they're anywhere close…”

“We started to hear from businesses that, oh, I'm scared of good search. I don't want a good search product in my company because I have all these governance gaps. I have like, you know, sensitive information all over the place.”

“People talk about hallucinations as a big problem with AI models. You know, we feel like, you know, a bigger problem for us is not even hallucinations. It's about Like, you know, most of the times you can't even, you know, find that information. Sometimes it's…”

“And one thing that's going to fundamentally happen is that each one of us is going to have this amazing team Of, you know, call it assistants, coworkers, coaches that are truly personal to you. And, you know, you're always surrounded by that team. And this tea…”

“We barely see any application where customers are running agents in a fully unattended unsupervised, you know, setting.”

“Now on top of that, you will have agents which will proliferate and they're going to be they're going to be like thousands of these agents inside, inside a large enterprise and they are all functional and they are, you know, vertical in nature.”

“We actually were not selling the product. We had no pricing. We had no plans to make revenue. That was an intentional decision we made that we were actually not even charged for our product for the first two years.”

“And the early movers will make the move first and then it will become a more normal thing.”

“So they very much, you should consider them an application level company, not just a model company.”

“If we look at our experience with as we go and prospect the, I think we would hear this answer more often that, well, like, you know, we are a Microsoft customer and we already have, you know, we're getting co-pilot. And so, therefore, like, it doesn't make se…”

“Now it's probably about almost a hundred percent. Like, nobody's actually, like, writing the initial code, you know, by hand anymore.”

“The real bottleneck has shifted from The person writes the code to personalize the review.”

“I think good technologies figure out how to make technology really, really cheap, and it's gonna happen here too. That's my belief. Like, you know, you're going to see it. You're going to see inferencing costs come down by orders of magnitude.”

“There's a power law, like, you know, in our company, and also at all of our customers, you will see some people who spend 10,000 dollars or 15,000 dollars in tokens every month, and then you have others who are spending 20 dollars.”

“But if you now start to talk about, okay, AI talent, ML talent top people are sought after, you know, way more than ever before. And also the pay scales have completely changed and not just from the model companies, but even from startups, because, you know, s…”

“I would say, like, our series C probably felt the most I guess you could say the most expensive, because we barely had any business, like, definitely, like, you know, sub two or three million dollars, maybe five million dollars, I don't remember exactly, but t…”

“I've always personally, like my style has been a little bit too disciplined to be the right strategy anymore. I get that feedback from my team that, you know, we are trying to be conservative. We're trying to make sure that our capital goes a long way. And in …”

“Well, the comp, comp composite roles will be will be very common. So like, as for example, you know, somebody who can build a product I don't know what to call them, but they can, they act like engineers, product managers, designers similarly in go to market Y…”

“The only Country in the world, you know, that has produced models outside of US is China. And then of course, maybe a little bit in, like, you know, France with Mistral.”