Arvind Jain

“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.”

“At one point we had a serious acquisition offer that we were considering. It was a big acquisition offer. We would have all made out very well.”

“At any given point, you have one question you're trying to answer, and you want to go get that answer. That's all that you need to make something work. Don't overthink it. The one question we have right now is not any of that shit. All we need to know is do cu…”

“Glean's an amazing company, and I have a lot of respect for Arvin, but it's so horizontal. Like it's a very powerful chatbot, and it allows people to build some agentic applications or systems of agents on top of them, but really the deep cross-functional cros…”

“Everybody in your company is probably using ChatGBD and Claude and other tools on a daily basis.”

“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…”

“What we tell people is that I think the winners are yet to be identified and so experiment with more vendors, do shorter term contracts.”

“I know we do think that the intelligence layer is actually going to be a pretty thick one. Maybe, you know, it's, it will capture half of the enterprise value.”

“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.”

“In, in Glean, we have this policy where we record every single meeting, internal meeting, external meeting if our customers allow because there's so much information, you know, in there.”

“The advantage that Arvin had was that he was previously the co-founder of Rubrik. So he noticed this problem at Rubrik, left Rubrik to start Glean, and he basically built Glean for Rubrik, right? And the bet that he was going to make was like, rough and tumble…”

“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…”

“Businesses are actually a lot more, more interested in, not in that, but in actually thinking about how they can transform their company with AI, how they can take specific business processes, you know, where they're spending a lot of money and how, how do the…”

“Everybody has been trained over the last 20 years to actually type in, you know, one or two keywords, like Google has sort of taught us, you know, on what search can do. So with search, we never had a problem. Like, you know, we launched our product, we had, l…”

“In Rupert, we're an established market, like the budget, several dollars, and you had to actually replace an old technology with a new technology. Here we were in a market where we had no budgets. There was no concept of buying a search product in the enterpri…”

“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.”

“The more you look at priors, the more you're going to actually, likely you're going to actually ultimately kill your own idea.”

“Even at Google, like, it was a big joke, you know, always we had internally, like, you know, All of us were spending all of our time making it easy for people to find things, but not us internally at Google. It's super hard to find anything inside the company.”

“Today, the, for most customer use cases the companies are using the closed, closed models at the moment”

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

“We need to have a way within, like, you know, 30 minutes to know how well it's going to do on our product, right? I mean, and you can do those things. You can actually build the right, you know, evaluation frameworks, things like that.”

“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.”

“And the future that I see with AI is that every person who works is going to have this amazing team of assistants, coworkers, and coaches around them that is going to actually make them a lot more effective.”

“We'll be back to Arvind Glean. We did it as a co-led it with Lightspeed at 35 post. And Arvind is a G. You know, he started Rubrik. He's like one of the, you know, Google fellow type of person. He raised a lot. He's like fifteen million at 35 post, so gave up …”

“Cause sometimes I feel like, you know, at Google, I was not feeling challenged anymore. Cause you know, we're such a successful company and we could always, you know, take big problems, you know, and work on them. And it didn't matter if they failed. Cause lik…”

“We actually tripled the size of the engineering team, but like, you know, still write, you know, the same amount of code.”

“Well, historically, like this is not a new problem, like helping employees find information at work. So there have been companies, you know, Google had a product too, and, but nobody really solved it in a way where somebody liked the product, somebody actually…”

“There were investors who would tell me like, you know, that they would back me, you know, because I've experienced building a company before, but they didn't want to back, you know, the idea that I was working on.”

“In fact, the more people I would talk to, like, you know, especially people who are, Who have business acumen, like they would actually turn, turn me farther from this idea. So I actually chose not to talk to too many people.”

“And I think it's important, like it's important sometimes not to overanalyze and actually focus on the use end user and the problem and just go and solve it.”

“Like, you know, sometimes we sort of talk to our team about it, so we didn't do any TAM analysis. Like, how do you do TAM? There's no product in the market. Nobody actually is even solving this problem.”

“I didn't actually go and, like, you know, hit my friends, you know, and say, like, hey, can you actually, you know, take this product and give me feedback? Because I felt like, you know, they'll all be very nice to me. And they will do it like, you know, even …”

“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.”

“Search requires a lot of R&D, lots of technology to be built. So we wanted to build a team of about 20 people and divide it into, like, you know, three different areas, you know, of our technology stack.”

“For a first time founder, like, you know, they're actually trying to, their goal is actually You know, succeed as an entrepreneur. They want to actually learn that, you know, that art. Sort of like, you know, it's personal in that sense. You know, for me, that…”

“When we saw that it crossed 10 searches per day on average, that's when we knew that, well, look, now people are dependent on this product. They are actually getting value from it. And that's when we felt, you know, we were ready, you know, to charge for this …”

“So we've been actually growing at about three to four X, like, every year in terms of multiplying our revenues.”

“So, so getting, getting to like I think the first year of selling, like we did three million dollars, if I remember right now.”

“Like, you hear these stats that nine out of 10 startups fail, and I like to tell them that, like, look, no, it's not nine out of 10, it's 99 out of hundred, because you didn't count all the first 90 startups that the founder killed themselves, like, you know, …”

“The governance is actually a big part internally. And so when you have these like tens of different AI tools coming into the company, all of them need to work with knowledge, your enterprise knowledge. And so if you start to just copy your enterprise knowledge…”