He quit his cozy Google job & ignored lean startup advice— then grew to $3M in 1 year. | Arvind Jain, Founder of Glean

Arvind founded 2 billion-dollar startups—by doing everything lean startup tells you not to do.

- He didn’t focus on launching an MVP.
- He ignored early market feedback.
- He didn’t charge beta users anything—  for 2 years.

And it worked.

He went from $0 to $3M in revenue the year he launched publicly. He tripled to about $9M the year after. And tripled every year since.

Two months ago, Glean raised $200M at a $2B valuation.

Why you should listen:
- Learn exactly how outlier founder Arvind Jain does things differently at the 0 to 1 stage.
- Why he thinks conviction and persistence are the most important qualities founders need.
- When you should follow playbooks and when to write your own.
- Why it might not matter that most people don't "get" your idea in the early days.

Timestamps:
(2:02) Leaving Google
(3:39) Coming up with Glean
(7:47) Building a Product in a Neglected Space
(11:38) Skipping Lean Startup
(14:11) Using design partners
(16:13) Building for 2 years, with 0 revenue
(20:13) When it's time to launch
(21:12) Why AI was a key tailwind
(26:25) Finding Product Market Fit on Day One
(27:32) One Piece of Advice

Transcript

Arvind: 0:00

My number one advice to founders is conviction and persistence. If you see a problem that's out there, then don't think too much about who else is solving it or how big the market is. Just go and solve the problem and persist and believe in it. There's going to be ups and downs. There's going to be enough people telling you that, hey, look, I see this problem, but I don't see myself paying for it. Don't worry about all of that part. If you think that it's a large enough problem, a lot of people face it, having that conviction and belief and staying on course is, I think, the most important thing.

Pablo: 0:35

Welcome to the Product Market Fit Show, brought to you by Mistral, a seed-stage firm based in Canada. I'm Pablo. I'm a founder turned VC. My goal is to help early-stage founders like you find product market fit. Arvind, welcome to the show.

Arvind: 0:53

Thank you so much for having me.

Pablo: 0:54

Listen, I've got your LinkedIn open right here. I'm looking through it. Ten years, distinguished engineer at Google. The claim to fame, as far as I understand it, is you made Google Search as fast as a blink of an eye. Then you go off, you start Rubrik. That actually is filing for IPO now. They're doing half a billion dollar on revenue, worth $5 to $10 billion, but that wasn't enough for you. You left halfway through that story, started Glean, which is what you're working on today. You just raised $200 million for that at over $2 billion valuation. My first question honestly is, what's the secret, man? What am I doing wrong?

Arvind: 1:27

No secrets. I would just say I've been so fortunate to actually be with people who want to build great products and achieve some success with them. Excited with what we've done with Rubrik, what we're doing with Glean.

Pablo: 1:41

Then let's dive in a little bit. We'll spend almost the entire episode on Glean, but just to get some context, walk me through just leaving Google, especially at the state that you were at. Obviously, let's call it, very comfortable position for a bit of a euphemism, but to decide to go off on your own and start your startup, what drove you to do that? Yeah, just walk me through that thinking.

Arvind: 2:02

I really enjoyed working at Google. I always got to get a chance to work on products that were really meaningful, that everybody around me uses. It was amazing. I had no plans as such to actually go and start a company. I was not feeling any unrest. Sometimes, problems come to you. In this case, my co-founder Bipul and I, we chatted about this problem that we ultimately built Rubrik for, and it was exciting to me. I just felt that it would be great to actually go and do something on your own, not have this… always have this big support system that you have behind. Because sometimes I feel like at Google, I was not feeling challenged anymore because we are such a successful company and we could always take big problems and work on them. It didn't matter if they failed because as an individual, yeah, you move on and you start a new project. Sometimes that also makes you dull. Here, it was actually interesting for me to actually see, okay, let me see what I can prove.

Pablo: 3:08

No safety net, burn all boats. It either works or it doesn't.

Arvind: 3:12

Yeah, and of course, it was the – we know that, if you succeed, that actually is going to feel totally special.

Pablo: 3:20

You go through this journey. Things are going quite well. I believe you raised this series E or so. This is the 2018, 2019 time frame. How does the idea of Glean come up? Then how do you work through – you're the founder. You're one of the founders. How do you work through exploring that and ultimately leaving? Walk me through that period.

Arvind: 3:39

We ran into this problem that Glean solves at Rubrik. We were really, really lucky at Rubrik to grow the business really quickly. In four years, we were actually more than a thousand people in the company, but with that growth came challenges. One of them was that our productivity actually dropped quite a bit. As engineers, they're not able to write as much code. Salespeople are not able to sell as much stuff. Overall, we felt that you're investing so much, we actually tripled the size of the engineering team, but still write the same amount of code. It doesn't matter how many people you bring in, you don't get more things done. We would run these surveys, poll surveys, and ask people what's wrong with the company. What are the things we can do better on? Always you would see this one problem that was top of mind for people. This was one of the, I think, default questions in the survey, which was that people would complain that I cannot find any information in this company. I don't know where to go and look for things, and I don't know who to go and ask for help. This was a big problem. When it became clearly the largest problem there, I thought about it and it resonated with me because I felt the same way. In fact, everybody in the company felt the same way. There's so much data, so much knowledge across so many different systems. Nobody knew what stuff was there.

Pablo: 4:58

Would you say that's even worse at a fast-growing startup? Just because if you think about zero to a thousand employees, that means most of them got hired in the last year. They don't even know what they don't know sort of thing. Was that exacerbated at Rubrik?

Arvind: 5:10

Yeah, it was definitely exacerbated because it was a fast-growing company. When we saw this problem, we wanted to solve it. We went and talked to a few other companies just to see if they were running into this problem, what are the solutions for this. We realized that this was such a common problem. Every employee and every company in the world struggles with this. They're struggling more and more as we’re going through this SaaS transformation where suddenly businesses started to use hundreds of systems and applications and your knowledge got really fragmented.

Pablo: 5:43

What was your role, by the way, at Rubrik at that time?

Arvind: 5:46

I was the head of R&D so I actually was responsible for all product development, but I was also, I guess, founder. I would also look at issues these internally, how can we make our company better. Initially, and I'm a search engineers, when I see that people can't find things, I say, okay, let's go and buy a search engine.

Pablo: 6:04

It's deep, yeah.

Arvind: 6:05

We tried to go and find one and I didn't find anything to buy. I was really shocked. I said this is such a commonplace problem. How come there is not even a single product that I can go and buy for this? That led to that initial thought process of, hey, maybe I should go and solve this. We thought about maybe I should build a second product in Rubrik, but it just felt like it didn't make sense for us. We were in such large market already with the small market share so all of our focus there had to be on our existing product.

Pablo: 6:40

Was that a tough conversation internally? You ultimately going to your other co-founders and saying, actually I think I'm just going to go off on my own and start something new.

Arvind: 6:49

It was tough for me internally first, before I even discussed with somebody. I had to figure out why, how, does it make sense, why? We actually built the organization to an extent where we had great leaders and they're doing great job. In fact, they're better than me. I felt I had the ability to do a really good smooth transition and start Glean, but I was so excited about it. It's a problem that is something that I feel is really fundamental. We believe that we make such a big impact on the lives of people who use our product.

Pablo: 7:26

Now, weren't there – just thinking through this problem, like you said, it was a problem that everybody faced. In a sense, it classified in the world of obvious problems that are just really hard to solve, but weren't there some – I remember Dropbox I think had put something out in this space or was at least marketing that they had a solution. Were there a lot of big names going after this problem as well?

Arvind: 7:47

Historically, this is not a new problem, helping employees find information at work. There've been companies. Google had a product, too, but nobody really solved it in a way where somebody liked the product, where the problem actually got solved. Overall, I would say it was more of a neglected space as opposed to a space where a lot of companies were thinking about doing something. When we came in, we built the product, we felt that we were the only ones who were truly focused on bringing assistance to employees with a product like ours. Most of our journey has felt more like creating the market for it as opposed to competing with other vendors with a better product.

Pablo: 8:30

Walk me through those early days. You finally do decide to leave Rubrik. My understanding is you raised that, I think it was $15 million round, right out of the gate. What was that process like? I assume, was it relatively straightforward just because of your background and what you've proven so far?

Arvind: 8:46

Yeah, the process of raising capital was relatively smooth, but I think it was interesting. There were investors who would tell me that they would back me because I have experienced building a company before, but they didn't want to back the idea that I was working on. There was some struggle because I think this was a difficult problem. There were no successes in enterprise search which is how people clubbed us as into that category, and so rightfully so, there was some hesitation from investors, but you always find, ultimately, there are great investors who have the capacity to actually take on big challenges. They're not afraid of all the risks.

Pablo: 9:31

What's the first step? You already validated the idea, so do you just go right into building the product? What do you focus on in those early days?

Arvind: 9:40

First thing first, right? I think, for me, the validation happened just it was actually something that was fundamental, something that just I believed in. I didn't need anyone to validate. In fact, the more people I would talk to, especially people who have business acumen, they would actually turn me farther from this idea. I actually chose not to talk to too many people.

Pablo: 10:08

How come? What would they say? Were they not aware? They didn't feel the problem themselves or was it something else?

Arvind: 10:14

Everybody feels the problem, but everybody felt that in those days that, hey, I can live with it. I can live with this problem.

Pablo: 10:23

Like a nice to have.

Arvind: 10:24

Yeah, I feel this is a nice to have. This is a vitamin. This is not a painkiller. I have a much more simplistic thought process. I don't think about those. I'm not a business person either, but for me, it was like I was going with the engineering mindset, which is that, look, I know all these engineers, they're spending one third of their time just trying to find things. They're frustrated and there's some value to be created here. Part of it was that, just that belief, and actually not just me, whoever we hired in our initial founding team and the people who we hired after that, all the people who came to work at Glean had the same level of belief in the problem that we're trying to solve. That's the only reason they came, that it's a problem that they faced in their work lives, and they knew it was important. They were also engineers. Initially, you hire engineers, so you don't think about the vitamin and the painkiller and the nice to have versus must have. That's not how you think users go and solve a problem. That's our initial journey is to – and I think it's important. It's important sometimes not to over-analyze and actually focus on the end user and the problem and just go and solve it.

Pablo: 11:38

It's interesting. A lot of these vitamins, they feel that until, like you said, you have the thing and then you realize you can't live without it anymore. Then it's effectively a painkiller because you create the pain, right? Did you do, I'm curious back then, you talk about over-analyzing, which this is a theme that I've seen through and through in so many of these early stories. Things work because people build something that solve problems and then the market presented itself. How much thinking did you do at the time of TAM analysis, market size, pricing, all these things?

Arvind: 12:07

That's a great question. Sometimes we talk to our team about it. We didn't do any TAM analysis. How do you do TAM? There's no product in the market. Nobody actually is even solving this problem. You had to really – basically my mindset was that this is fundamental. Initially, when people are – investors ask me, okay, what's the TAM or how big is this opportunity? How would you even figure out how much people would pay for it? What should be the price and what's the ROI? How are you going to prove the ROI? You won't be able to prove the ROI because saving time is so nebulous. My question to them would be always that, okay, think about email. Do you think you need email in your company? Nobody doubts it. I said, what's the ROI of it? Nobody can come up with the ROI either.

Pablo: 13:00

Slack was a great one like that. I remember when it came out, we were paying, we were a startup paying for Slack, and our CFO was like, you guys really need to pay for this? I'm like, yes, do not take this out.

Arvind: 13:10

Some things are fundamental and we felt that search is like that. Look, you're trying to find things and to get work done. It's important. Then especially in this new world where knowledge is exploding, every year you double your knowledge inside your company and you spread that knowledge across 30% more systems at 300 different places. Enterprises have thousands of applications and all your knowledge is spread across all those places. How are you going to find anything? Just like on the internet, think about the internet. Are you keeping track of like, hey, if I'm looking for a recipe, I'm going to go to this place. If I want to look for news on certain topic, I'm going to go there. You don't do that. It's not possible anymore because there's so much information. It's across so many different places.

Pablo: 13:58

You got now this core group of engineers. You have the funding. You need to build the product. Do you just go heads down and build or do you partner with some design partners to figure out the subtleties of it? How do you make that MVP work out?

Arvind: 14:11

You absolutely have to have people. There's no way to build a product, especially like this one, without any design partners. That was the first task. As we started to think about technology, I was, although I'm an engineer, but I had all, any non-engineering task, whether it's ordering coffee for the office or figuring out design partners, those are my tasks. Actually, it's very interesting. I followed a very different process than typical. I didn't actually go and hit my friends and say that, hey, can you actually take this product and give me feedback because I felt they'll all be very nice to me and they will do it. Even if they don't have a need. I actually went on LinkedIn and I would actually do call outreach to people, and I would like, look, I'm building a product this. Do you have this problem? If you have this problem, I would love to talk to you and get your feedback so that I can build my product with direction from you. That was the journey that we went through. Did a lot of –

Pablo: 15:13

Do you remember the specifics of that? I'm curious. Did you have to send 100 of these to get 10? Do you remember how high level, how much volume you need to go through?

Arvind: 15:21

Yeah, I had to do a lot. I don't think I was getting one out of ten responses. Maybe I was initially, but then I was the BDR for my company for the first two years. The response rates would be low. I've sent thousands of outreaches. I'm looking for – and I understand everybody's busy, but when you get the response, that's from a person who has that pain because they're responding to somebody who they don't know, right? Somebody who has no brand in terms of nobody knew about our company, but so that means the problem must mean something. The problem is an acute pain for them because that's when they're responding.

Pablo: 16:02

To be clear, your message wasn’t, hey, I'm building this thing. Do you want to buy it? It was very much, you might have this problem, let me ask you a few questions. That’s how you framed it in the early days.

Arvind: 16:13

Yeah, it was never about selling. Those outreaches were never about selling because in fact, 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 would actually not even charge for our product for the first two years.

Pablo: 16:26

I'm curious. In those two years, how did you structure the team? Because you can easily, given the funding you had, I mean, you could build a very big team or you could keep it small, five to ten. I'm just curious how you structured it.

Arvind: 16:38

We got the team to about 20 people. That was our goal, which is large. Sometimes for companies you don't start that way, but we knew that this is a difficult problem. Search requires a lot of R&D, lots of technology to be built. We wanted to build a team of about 20 people and divide it into three different areas part of our technology stack. We felt that that was basically a good team to actually make a lot of progress and build a great product. Then we stayed there. It was like I would say we got to about ten people within the first five months. Then gradually we got to 20 over the next five months. By the end of the first year, we were more than 20. Then we stayed out there for some time. There was a sufficient strength that we had in our engineering team to keep making a lot of progress.

Pablo: 17:28

You mentioned taking a different approach. I mean, I can see it because if you go for two years building a product without necessarily charging for it, you're certainly not following the Eric Ries Lean Startup, fast iteration, MVP approach. Why not? Why didn't you just build the MVP, the lowest thing that somebody would pay for, put it out and just do what most startups tend to do?

Arvind: 17:45

Yeah, because we had a fundamental belief in the problem that we were solving. We didn't feel we had to pivot. Our journey was not about that we are going to actually try something, we're going to learn something, we're going to change it and irate. Sometimes we talk about product market fit here. For me, I think there was something about this problem. I had no doubts that we will solve this problem, but I also was aware listening to customers, we can get a lot of different ideas. There are some decisions that you have to make, which are fundamental yourself.

Pablo: 18:19

That's pretty incredible. I'm trying to make sense of it. I mean, there is analogies, right? If you look at hardware as an example, whether you take the iPhone or now the Vision Pro or whatever, you just can't iterate at that level. You have to have – you of course talk to customers, but at some point, you got to have that leap of faith, that conviction that puts you in a room for two years, so to speak, and builds a thing that really delivers value. I guess the challenge is when you, let's say, go against the grain. In your example there, the market's saying one thing, you're like, no, I'm sticking on that vision. Obviously, you might end up two years later and the thing you built, nobody wants. I'm just curious how you think about that. How do you balance that? Even your advice to founders, because on the flip side, the Lean Startup method is so ingrained that almost everybody is just blindly running that motion. Maybe in some cases it just doesn't apply.

Arvind: 19:05

Part of it is actually what is the goal that this founder has. Is the goal to actually build a successful company or is the goal to solve a problem, something that you're passionate about? For me, it was the latter. I was not trying to get a win. I was actually trying to solve that problem. That's why we made those decisions. We want to actually bring help to every single person. We want to make work more exciting. We want to make work less frustrating for every single person in the world. For a first-time founder, they're actually trying to – their goal is actually succeed as an entrepreneur. They want to actually learn that art. It's personal in that sense. For me, that was not what I was looking for. For me, my focus and to date now, all the decisions that we make even today are driven by that thing, which is we want to actually solve this particular problem for people.

Pablo: 20:02

As you're doing this, what's the threshold where you do launch? What are you trying to get to where you feel like, okay, this product is ready to be sold?

Arvind: 20:12

Yeah, so as we said, for the first two years we didn't charge. We wanted to see engagement. We wanted to see how much people are using the product on a daily basis. When we saw that it crossed ten 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. That's when we felt we were ready to charge for this product. In our metrics, we're showing that both that they are actually finding things that they need and also they're actually using the product a lot. They're finding it useful to actually come and search here as opposed to using their old methods of finding.

Pablo: 20:54

By the way, what was so hard about this product? Do you remember as you went through that development cycle parts that just were really hard to make to work properly or even places where you might've thought I wonder if we can actually get this to the vision that you have?

Arvind: 21:12

Well, I mean, if you think about search, it is like magic. You can come in and ask any question and now we have answered that question for you, doesn't matter what question you came and asked. It's a difficult thing. You have to now think about this, just imagine the process of how are you going to actually solve this problem. First you have to actually connect Glean with all of your company information and data across hundreds of these systems that you have, all of them with clunky APIs or interfaces and data models. You have to bring information from all these different systems. You have to normalize it. What information is stale? What is out of date? When you answer questions for people, don't show them stuff that's no longer source of truth anymore. You have to think about how do you semantically understand data and knowledge because people are not going to be – you want people to be able to ask answer questions very freely in natural language. They can use terms that don't exist in the documents. There's a lot of technology that goes behind the scenes to actually build a product this. We've seen this. We've seen how complicated the Google Search stack was. Most of it actually did come from Google. We worked on search there. We understood the complexity of it. Then we had to think about the security aspects of it, which is that – imagine this, I go to Pepsi or some large company and tell them that, hey, look, we have this great search product. What we need is we need you to give all of your data to us. Then we'll actually make it searchable for you. They're going to wonder, okay, who are you? No brand company and you want all my access to all my data? That's an issue. If you start to think about the problem, although the problem is actually very meaningful, there are a lot of challenges.

Pablo: 23:08

How much did the advances in AI, like LLMs and all these sorts of things, did that play into what you were able to build at Glean? Was that a tailwind for you guys?

Arvind: 23:17

Absolutely, and actually, it's always been part of Glean. Even on Day 1, our product, we're using LLMs. Now, of course, everybody talks about LLMs and we've all seen how powerful they are, but they were actually, initially, all of this research happened in Google and LLMs were actually, or these language models were actually built with one purpose, which is to make search better, to make Google Search better. When we started, we were actually able to use these BERT family of language models that Google had actually published in Open Domain. These were language models that were trained on all of the world's knowledge. They understood things like a user manual and a product guide are semantically equal and things. This model actually has all of that language understanding buried inside of it. We were able to use these models from Day 1 to build a really smart semantic search experience. We were doing vector embeddings and now everybody calls this vector search. There's no name for it like when we were using it initially. The journey has been a continuous one for us. It's not that four years later we realized that there's this massive new language model thing and we need to change our stack with it. We're progressively using it. These models just kept getting better and better. It allowed us to actually also make our product better. Initially, it looked more like the traditional Google where you come and ask questions and we'll surface that information back to you. The technology has been amazing enabler in terms of making a product better, but it's also amazing for us in terms of helping us push our business. This is where the transition happened from the vitamin to the painkiller. People saw that if only I had something like Chat GPT inside my company or all of my company knowledge, people realized that, whoa, no, this is something I absolutely have to have.

Pablo: 25:09

It makes sense. I think a lot of these products that are step changes you only realize later how much of a painkiller they are. I mean, Google itself, search itself is that. I'm sure before it, you ask people, hey, you could ask a million different questions a day, you’d be like, well, I don't have that many questions. Then you realize you do and you just constantly, everything that pops in your brain, right? Let me ask this final question. You take these two years. In 2021, you raised the $40 million series B. My question is, around that time frame, I mean, once you launch this product, how fast did revenue grow? How long did it take to get to $1 million in revenue or $5 million in revenue? Do you remember those days?

Arvind: 25:43

We've been actually growing about 3x to 4x every year in terms of multiplying our revenues. We probably hit, right after we launched, because we did have a good set of design partners. There's a big pipeline that was already built for us. I think our first year of selling, we did $3 million, if I remember right.

Pablo: 26:06

Perfect. Well, we'll stop it there. I appreciate you taking us through the journey. I'll just end with two questions that we always end with. The first one is, I mean, in your case specifically, you understood the problem deeply, but I'm still curious, when did you really know that you had true product market fit?

Arvind: 26:25

I think I knew it on day one. I mean, that's it. I knew that we were going to go through this challenge of trying to convince people of the value of the product, but we were ready for that. We were ready to actually build our team, evangelize, and convince people because there's never a doubt in my mind that the people want this product. Whenever I go and talk to anybody, they tell me they want this product. Then there's no doubt. It was just a matter of cultivating the market. We thought that the journey would be slow, but in the sense, if we had to constantly go and create the market, evangelize, it changed in the last 18 months and now suddenly we have something that everybody in the world wants. It's accelerating us and our business.

Pablo: 27:14

Perfect, and the last question is after going through founding Rubrik and now founding Glean and creating two multi-billion-dollar companies, what advice do you have, taking everything you've learned, for first-time founders that are starting, or maybe not even first-time founders, but founders that are starting something new today?

Arvind: 27:32

Yeah, I mean, my number one advice to founders is conviction and persistence. If you see a problem that's out there, then don't think too much about who else is solving it or how big the market is. Just go and solve the problem and persist and believe in it. There's going to be ups and downs. There's going to be enough people telling you that, hey, look, I see this problem, but I don't see myself paying for it. Don't worry about all of that part. If you think that it's a large enough problem, a lot of people face it, then having that conviction and belief and staying on course is, I think, the most important thing. As engineers, a lot of times, founders are engineers and our mindset is to doubt. I tell people, you hear these stats that nine out of ten startups fail. I like to tell them, look, no, it's not nine out of ten. It's 99 out of 100 because you didn't count all the first 90 startups that the founder killed themselves. Sometimes we say the startup – but most of them fail in the mind of the founders. If there's a problem and you can solve it, then it doesn't matter who else is out there.

Pablo: 28:41

Perfect, love that. Well, Arvind, thanks a lot for spending the time. This is great.

Arvind: 28:46

Appreciate that. Thank you for having me.

Pablo: 28:48

If you listened to this episode and the show and you liked it, I have a huge favor to ask for you. Well, it's actually a really small favor, but it has huge impact, but whichever app you're listening to this episode on, take it out, go to Product Market Fit Show and leave a review, please. It's going to help. It's not just going to help me, to be clear. It's going to help other founders discover this show because the algorithms, whether it's Spotify, whether it's Apple, whether it's any other podcast player, one of the big things they look at is frequency of reviews. It's quantity of reviews. The reality is, if all of you listening right now left reviews, we would have thousands of reviews. Please take literally a minute, even if you're just writing great podcast or I love this podcast, whatever it is, just write a few words. Obviously the longer the better, the more detailed the better, but write anything, leave five stars and you'll be helping me, but most importantly, many other founders just like you discover the show. Thank you.