In our latest Dev Propulsion Labs episode, we hosted Harjot Gill, CodeRabbit’s CEO and co-founder. He shared his vision regarding the current state of the industry and what it actually takes to build a fast-growing AI devtool.
He also told us a story about going viral in Japan, how that organic growth showed him there was a real market need, and what he did next. Plus, why AI code generation doesn’t make code review obsolete, how open source became CodeRabbit’s best GTM channel, and why the old startup playbooks no longer apply.
Watch the full video on YouTube.
Transcript:
[00:00:00] Victoria Melnikova: Hi everyone, this is Dev Propulsion Labs, a podcast about the business of developer tools and my name is Victoria Melnikova. I’m the head of new business at Evill Martians, and today, uh, I’m in a new setting. I’m at CodeRabbit, and we will be interviewing Harjot Gill and co-founder of CodeRabbit. Hi Harjot.
[00:00:25] Harjot Gill: Hi Victoria.
[00:00:26] Victoria Melnikova: How are you today?
[00:00:27] Harjot Gill: Pretty good. Thanks for coming.
[00:00:29] Victoria Melnikova: Thank you for having me, and we’re in this gorgeous studio. I’m not sure if it translates, but it’s kind of jaw dropping. The views are crazy here. And I want to talk about CodeRabbit, and before we dive deeper into it, I want to kind of give an overview of the landscape where CodeRabbit sits.
And CodeRabbit is an AI coder view tool, right? And with it kind of. Pre-phase, the whole AI wave. So right now everything [00:01:00] is very different from what it was two years ago. Hard job. Maybe you can tell us where’s Codera today? Who are you serving? What’s, well basically, what’s your short pitch these days?
[00:01:12] Harjot Gill: Yeah, thanks. So we started on two and a half years back and one of the biggest use cases for generative AI has been coding. Around two and a half years back, we saw like GitHub copilot emerge with a really convincing, like auto complete that was a step up from tab nine and earlier. Auto completes AI based auto completes in the past, and then we saw like rise of cursor, the tab completion models, and then fully agent software develop development lately, like with cloud code, code Codex, those kind of solutions leading the way.
[00:01:44] Victoria Melnikova: Yeah,
[00:01:45] Harjot Gill: so code rapid, like. Focused on a slightly different pain point. Saw that as a volume of code is going to increase with generative ai, the software development is getting more and more, at least part of software development is getting automated. Not the whole thing. The bottlenecks are [00:02:00] going to shift towards understanding the code changes that the AI is not making for you.
The code reviews will become a bottleneck, and that’s what CodeRabbit does the best. So we are the leading product in that category that provides code reviews, whether it’s a human written code, and now increasingly it’s all AI generated code, and we provide feedback around enforcing best practices of finding security issues, PII, leakage and so on.
Also allowing organizations to enforce their own guidelines and policies.
[00:02:31] Victoria Melnikova: So something that I, I talk to founders a lot about is that engineers are quite conservative buyers and sometimes it’s really hard to get their buy-in on certain. Progressive technologies. It sounds ridiculous, but that’s what we find.
And at times it can be hard for engineers to adhere to new practices and really break down the kind of like the concepts on which their development flows are built. Especially, it’s hard for them to let go of [00:03:00] control, you know? And code review is something that allows you to, to have control over things.
Right. So when you are pitching to developers as a company, what is the best optimal way to pitch products like AI code review to a developer and what has been really working for code rather than in winning them over?
[00:03:19] Harjot Gill: Historically, yes, developers have been a very hard audience to sell into. Like this is my third startup.
I don’t know whether, you know my story, like my first two startups are focusing a lot more on operators and SREs because mm-hmm. Typically the budgets tended to be a lot more on the production side. We see the development side and people have been trying to monetize SDKs. That never works. I mean, a lot of stuff is open source driven.
[00:03:42] Victoria Melnikova: Yes.
[00:03:42] Harjot Gill: In that community. Right. And which has changed a lot with ai. We are seeing there’s a massive appetite to pay for these AI products, like even code editors. Were very hard to monetize in the past, like sublime and all. You know, like there were many attempts to monetize editors, [00:04:00] but now you’re seeing everyone’s paying for either cursor, cloud code, even terminal tools, right?
So that has changed a lot because there’s a big step function improvement in productivity. For this dev tooling, like Dev tooling is right now a really great time to be in this space. Yes. On the other hand, Codera focuses slightly less on individual developers. I would say it’s focuses a lot more at the team level, so we are like a central quality gate that you as an organization want to implement the guardrails as your developers are adopting generative ai, at least in our category, even pre gen AI people were paying for the tools.
If you look at. All the CI ICD tools or security scanners like Snake or soq or Sam grab pe. The, there were like some budgets there already, but what we are seeing with the code generation space that I have not like seen that in the past, like now people are monetizing even vs. Code forks.
[00:04:53] Victoria Melnikova: Yes.
[00:04:53] Harjot Gill: I mean, I mean it’s been around forever, but now like suddenly people are willing to pay for even code editors and, and so on.
[00:04:59] Victoria Melnikova: Okay, so [00:05:00] with the tools like cursor and code, code, et cetera, why does it still make sense for people to, to pay for a standalone AI code review tool? What’s the, what’s the mode?
[00:05:11] Harjot Gill: So code, I provide the guardrails, which is similar to, I mean, my analogy would be like coming from the operation space, it’s like Datadog, you have to pay for monitoring, right?
And what we are seeing in this space increasingly is that on the code generation front, mm-hmm. Like the developers are increasingly. Picking up the tool that they want to use. Like some people are more comfortable with IDE Form Factor Cursor while others are okay with now Terminal. Now there’s a Codex app that a lot of people within our company are liking.
Some people just want open source, so they are going to use open code. So what we are increasingly seeing is that on the code generation side, there’s gonna be a lot of fragmentation. So if I’m an organization, I don’t want to, like, if I have a thousand person engineering org, I don’t want to like go down and top down make a decision that everyone uses Wind server or cursor.
So [00:06:00] increasingly you want to give people choice. Mm-hmm. Both on the models and the hardness. When that happens, then the quality gate has to be centralized. So tools like CodeRabbit are going to be a standalone category in that world, just like Datadog was, like Amazon had CloudWatch or GCP had whatever stack driver, but in the end.
Datadog became a standalone product category. And even though like your Kubernetes, for instance, makes your, your services don’t crash, but doesn’t mean you take Datadog away, the guardrails will always remain. So same thing we are seeing here, like even the code generation quality is increasingly becoming good enough.
Like as long as you can control the intent, like the, the outcome on the, on the coding front is becoming really good. But the thing is that that does not mean your guardrails go away. Like the organization still need to bring everyone through a consistent quality gate. Enforce all their policies that they care about through that choke point.
[00:06:48] Victoria Melnikova: Let’s talk about business a little bit. What you described just now is kind of like inventing a new category in developer tuning, right? And that’s something that is a known phenomenon [00:07:00] in go to market for developers. So when we think about CodeRabbit, you guys have this initiative where Coded Drive, it is free for open source creators, right?
And. I understand why developers would love that and would be willing to try it and adopt it in their workflows, but at the same time, that imposes a question of how do you convert your open source users into paying users. So from the business perspective, do, do you have a stance on that? How do you kind of like sit on both chairs?
[00:07:31] Harjot Gill: No, that’s a great question. Like, I mean, I mean I personally have been like a big fan of the open source community. Mm-hmm. And the maintainer especially who do a lot of thankless work. To keep these projects running. So we started like even in the previous startup sponsoring some of the projects that we used internally.
So it’s a way of giving back. For example, CodeRabbit is built on a lot of like different like static analysis tools, like Get Leaks and all, and we go sponsor even these smaller projects, they may not be like thousands of stores, but just because we rely on them. For example, [00:08:00] we were very early sponsors of a ST Grip.
Mm-hmm. So we were incorporated a ST Grip two and a half years back. And this was like still like less than 2000 stars at that point. So we always like make it a point to go back and sponsor those projects. The other thing of going back to the community is to give the product for free to these open source, but it also helps us in a big way.
Two things. One is like the other developers, which are like working in their enterprises or bigger companies that discover us. Through these libraries and frameworks that use us to maintain code quality. For example, like a lot of people discover us through all these, like I know TRPC project, I mean, and, and OpenShift.
They all use US Linux Foundation projects use us. Mm-hmm. And video uses us in a big way and open source. So there’s a lot of discovery happening. So instead of paying for Google ads in a area like giving these maintainers like a really great tool mm-hmm. Which saves them a lot of time as they’re doing this volunteer work.
At the same time, it’s an advertisement for our product. The second thing it does, and that is one of the reasons why Corab is [00:09:00] a very high quality product compared to a lot of the other people who are trying to do this in this space, is the feedback loop. Mm-hmm. Um, the thing with the AI and the AI harnesses is you need the data to improve.
So with the open source, because the data is public, so we are able to go and train fine tune and even like adjust our hardness because you have to mash the models with the, with the hardness that you’re running on top. So open source becomes like a really critical playground for us. Mm-hmm. Like when we are launching new models, we first, it leads you to open source with constant feedback coming in, allowing us to then roll it out for the paid users.
We don’t necessarily monetize our open source users into paid. In some cases we do, like Red Hat is a customer, for example, Nvidia as a customer. But we don’t like, in a general like see that as a path. It’s more like awareness for us, more like marketing.
[00:09:50] Victoria Melnikova: With your previous startup, you saw the GitHub copilot, right?
You saw the potential in that in, in code generation, basically. You kind of saw it before it became the mainstream. [00:10:00] What allowed you to stay on top of the wave? Because I remember like earlier in 2025, it really felt like it’s a wave that’s crashing a lot of startups because new players are emerging. The marketing is extremely aggressive.
You have to do a lot of field work here in SF to make sure that you stay on top. What were the key pillars that Cori relied on to not only survive, but come out on top?
[00:10:30] Harjot Gill: It’s a lot of this has to do with the, the foresight and where the market is gonna head and which battles we are gonna pick up and not gonna pick up.
So when we started the big questions, even the VCs had. Like how much is a model versus application?
[00:10:47] Victoria Melnikova: Mm-hmm.
[00:10:48] Harjot Gill: Like there’s a lot of like pushback that these products are just wrappers. But if you’ve been in the industry long enough, you know the value’s gonna accrue always up the stack. The lower level layers will always be commoditized.
In [00:11:00] fact, a launch block back in 2023, talk about why we will only focus on apps and not bother with the models. Right. And in hindsight, that was a great call. Mm-hmm. Because Asian hardness is, is where all the value is. If you look at cloud code and all, like model is one part of it, but also Asian hardness is, is the, the ux, the human AI interface.
I mean those will matter a lot more. So that was one focus area where we said, okay, we are gonna just be a pure application applied AI company.
[00:11:27] Victoria Melnikova: Mm-hmm.
[00:11:28] Harjot Gill: Right. And do a great job at that.
[00:11:30] Victoria Melnikova: Yes.
[00:11:30] Harjot Gill: Right. So some companies are taking more vertical approach. They’re like owning the hardness and the model. So that’s also, it’s like Apple versus Microsoft strategy in the pc, if you remember that.
Yes. Like Microsoft said, I don’t have to do what Dell does or Intel does. We’ll just do the apps, build Microsoft Office or whatever. And then there’s Apple that said, okay, I wanna own the hardware as well, which is in this case model, for example. So both strategies are correct, but as a company we try to do the other thing a lot more like focus just on the application layer, the context engineering part of it, the UX part of it, [00:12:00] and launching more products on top of it.
The other part is the insertion point, like, I mean, we feel that our strength is more on the background agents and the central insertion points. So we didn’t like optimize our product for speed, for example, we never said that we will go and compete with cursor and code generation startups. That is not a battle, which is of any interest to us.
And, and the products over there are also engineered in a different way. They’re designed to be fast, more like, I mean, they’re more biased towards like faster responses and more interactive workflows compared to our product, which is more often background agent, like code review takes like 10, 15 minutes to run where we can like apply the best reasoning models mm-hmm.
And so on. Mm-hmm. So a very different product strategy, insertion strategy. Even like the problem statements that we are focusing on as the next series of products are getting launched are very different than the market, the, the, the larger market is doing.
[00:12:54] Victoria Melnikova: So when you decided to incorporate CodeRabbit, what were the metrics that you were looking at or it was kind of [00:13:00] like.
You knew for, for certain that it’s gonna play off because that’s where the industry is headed and you just went all in.
[00:13:07] Harjot Gill: Right? I mean, this is where a lot of it is, like your intuition, like, I mean, I’ve seen failures as well. My second startup, for instance, we thought industry would be going in a certain way with upskill engineering, but did not.
So some of these bets sometimes take off, sometimes they do not like, but the main thing is you have to make a bet.
[00:13:21] Victoria Melnikova: Yeah.
[00:13:22] Harjot Gill: Like you have to be in the arena. Right. So that’s what we believe in. I mean, one analogy is like, it’s like being in Hollywood. We have to produce 10 movies, like maybe two or three will be super hit, make all the money back.
Then two or three are break even, and then some are flops. That’s how we see the space, like especially in the AI space where a lot of these form factors and products are still to be discovered. Look at this, like very recently, this person sitting in Austria build this CLO bot, which became open block.
[00:13:49] Victoria Melnikova: Yes, yes, yes.
[00:13:50] Harjot Gill: Now you had like all these model labs, you had ton of startups trying to build those things, personal assistance and so on. Now this guy goes and unlocks a form factor, [00:14:00] which was very different, and then it took off, which what this tells us is there’s so many products still to be discovered.
Like the models are really great, but even the model labs themselves don’t know what’s the best way to apply them or what the UX should look like with human AI interface and, and the insertion points. Right. And I believe like there’s still like so many products out there waiting to be unlocked and the value unlocked through those products.
[00:14:24] Victoria Melnikova: You started CodeRabbit two years ago, right? Three years ago almost.
[00:14:29] Harjot Gill: Yeah, almost two and a half, three years ago. Yeah.
[00:14:31] Victoria Melnikova: Yeah, yeah. And. The speed at we at which the, the VCs invested in, in AI products wasn’t as high as right now. Right now, I would say that you, we see bigger checks and bigger expectations from a lot of startups, right?
They, they have to show certain, I wanna say skyrocket and growth to, you know, to. Make their case. Do you feel like the same pressure applies to CodeRabbit or you’re kind of like over [00:15:00] that hype wave and you’re just cruising?
[00:15:02] Harjot Gill: It’s partially like even we have been raising significant capital, some companies have, are raising more, especially the ones which want to go after models themselves, like by GPUs and hardware to support training.
[00:15:14] Victoria Melnikova: Mm-hmm. Mm-hmm.
[00:15:16] Harjot Gill: And some of the VCs have the appetite for larger checks, especially in the AI space. Yes. Like a lot of VCs have raised ton of money, billions of dollars to invest in AI fundamental infrastructure as well as the startups on top of it. And we have seen this Cambrian explosion of startups, different form factors being tried, and some of them are going to stick and become generational companies right now is such an inflection point.
For example, like the next Amazon or Next Apple or Next Microsoft is already being founded or has been founded, and that’s what the VCs are looking at. It’s a, it’s a land grab right now. Very interesting time for to be either a VC right now or to be for startup founder.
[00:15:55] Victoria Melnikova: Yes.
[00:15:55] Harjot Gill: Right. Best time in, I mean, this is my third startup.
I said like, I’ve never seen anything like it. [00:16:00] If someone is thinking about starting a company, now would be the best time.
[00:16:03] Victoria Melnikova: Yes.
[00:16:03] Harjot Gill: Right. And then the the, then the market gets slightly challenging. Like right now, even the low hanging. Ideas are becoming massive in terms of revenue growth and then the bar is going to be higher as you wanna enter this space.
Like it’s almost like how Amazon like started by selling books on internet became massive. It’s simple. Like you had Cursor, which was simply a VS code for, I mean not a lot of tech there actually, but then became massive. Now they are able to invest in the tech, their own models and so on.
[00:16:30] Victoria Melnikova: Mm-hmm.
[00:16:30] Harjot Gill: But the idea was very simple.
A vector database, a VS code for simple UX command K interface. Mm-hmm. It’s not very complicated. It became massive. It’s just right place at the right time, at the right team.
[00:16:40] Victoria Melnikova: And I mean, with Cold Rabbit Series B 60 million, it’s still a sizable check, right? Like it’s a, it’s a big round. And do you feel like there is pressure to raise more, to raise, faster to raise and you know, to have shorter runs between the The funds?
[00:16:55] Harjot Gill: Yeah, it has been very short runs. Like we, for example, like at Cora, we didn’t do any seed round, [00:17:00] so we went to a million a r just on bootstrapping. We did a 16 million a round. Back in 2024. Yeah. And less than a year after that, we did a 60 million BR. Yes. So in a normal space, you will have a little bit of couple of years and more time to grow the team, get some repeatable numbers, like numbers that make more sense to the investors.
But this space is slightly like fast moving and the, the, the, the time between the rounds is, is very compressed. So that’s, it’s a very compressed timeframe. We are working with now. We are already like halfway between B and C. We are actually more than double or the revenue we had at B stage. Think about it, right?
And it’s like doubling very quickly every few months. So when you’re doubling that fast, you have to grow the team as well. It’s not like with the ai now you need a smaller team.
[00:17:48] Victoria Melnikova: Mm-hmm.
[00:17:48] Harjot Gill: Right. I mean, even Cursor and all those companies have grown to 350, 400 employees by now. We are almost also like 150 employees now, right?
Mm-hmm. So yes, you still have to have the people on the ground to [00:18:00] make the customer successful, right? Yes. With these products. So that’s the reason we are grab raising money. So it’s still like big, massive pool in the market.
[00:18:08] Victoria Melnikova: Mm-hmm.
[00:18:09] Harjot Gill: We try to buy. And the second is the opportunity to also build more products from our vantage point.
Like not just stop here, but can we now solve the next problem in this space? Find the next form factor.
[00:18:21] Victoria Melnikova: Mm-hmm.
[00:18:21] Harjot Gill: Right. And we have seen, like the products are still getting discovered, like cloud code, for example, like 12 months back, they, there was nothing like agent development. Mm-hmm. Like the Asian, the, the, the.
Edit code editing with AI was very simple, like Cursor had a composer product, not the model, but it was very simple, like few files in front of you getting edited with a prompt. Then cloud code comes in and introduces a form factor that blows everyone away, that you can just start with instruction and it goes back and explores the file and makes the changes for you, right?
And now no one can go back to the tab completion on the board. Most people have moved off it and just like that, like [00:19:00] more and more product form factors are still to be discovered.
[00:19:03] Victoria Melnikova: So what are some of the growing pains? Growing the team is hard, right? Especially when you have to hire 50 people. You know?
It’s like, and there are different specialties and obviously you are an experienced founder, right? Like you’ve seen that time and time again, and probably there are some lessons that you take from one startup to another. If we talk about the growing pay pains of today’s CodeRabbit, what’s the. The most painful challenge for you?
Is it finding like specific people or is it something else?
[00:19:33] Harjot Gill: It’s always hiring. Right? So because that makes a big difference, especially when you are like laying the foundation of all these business areas that you wanna build. Mm-hmm. And a company like us, like we are seeing the demand from small teams, like in an individual, developers buy the product five P percent team to teams, which are like 10,000, 20,000 developers.
So it’s a whole spectrum of customers. The buying behavior across them looks very different. So we are kind of like running multiple companies in [00:20:00] one, right? Where back in the day when I was doing your first startup, you had like New Relic on one end of the market and AppDynamics on the other. You do like other enterprise sales or PLG.
We, on the other hand, are running both strategies at the same time. So it’s complex like finding the leaders who could appreciate both PLG or enterprise and finding people who can be experts in one area or the other.
[00:20:22] Victoria Melnikova: Mm-hmm. Like
[00:20:23] Harjot Gill: getting those leaders has been big challenge on the engineering side as well, because the development software development has been transformed.
So people who can leverage ai, especially the people who are not like, I mean who are just graduating at all, like they are like more accustomed to like picking up these new tools and running with it. We have seen that as well. So we’re trying to like build a team, which is a mixture of like a lot of experience on systems building.
[00:20:45] Victoria Melnikova: Mm-hmm.
[00:20:45] Harjot Gill: While also people who go, who are willing to experiment and, and, and hack do the these hackathons and try these new products all the time. There a lot of experiments running at any given time at Codera and some of them like make it out as products. Others are just like [00:21:00] proof, proof of concepts that, that are very interesting.
Proof of concepts that people are building.
[00:21:05] Victoria Melnikova: So as the team grows, how would you identify like an ideal CodeRabbit employee? Who is that person? What, what are some qualities that they have?
[00:21:16] Harjot Gill: A lot of the things that boil down to, especially in a fast moving space like this, is, uh, a lot of the experience they have in the past doesn’t always translate to this space.
Even. I’m coming from a space which was very infrastructure, so curiosity and like just a humbleness. The work ethic. So those kind of things matter. Like can people move fast? It’s okay. Like we are driving like an F1 car, like we’ll crash yes from time to time, but the idea is that you have to think like a pro racing driver versus a driver who drives in a steady street.
So a lot more risk taking. So those are the good qualities. Even the organization building we are doing is, is unlike anything we have seen, like in most companies. Your marketing is expecting, I don’t know, 30, 40% growth a year. We are seeing that kind of a great month. Mm-hmm. In a month [00:22:00] or so, like 20 to 25% sometimes.
So, so it can be crazy like how you are, like the strategies that you’re running and, and the pace you’re progressing is, is just mind boggling here.
[00:22:11] Victoria Melnikova: You mentioned that 20 25, 20 26 is some of the best time to start a company. Obviously it’s very stressful because there is a lot of pressure on the market, but also a lot of opportunity, right?
Like chaos is a ladder. There’s a lot of opportunity here. As an advisor, if you were to talk to somebody who is just thinking about creating a startup here in sf, it’s kind of like a request for founders from yc, you know, what are some niche kind of opportunities that you see that have high promise?
What would you advise to pursue?
[00:22:44] Harjot Gill: Yeah, I mean, that’s always a challenge. Like, I mean, given how fast the space is moving, some of these ideas, if they’re like just one or two months out, they get subsumed by the larger players or get copied. Even the model labs, as we have seen, especially in the coding space, they have aspirations to go build products in the [00:23:00] coding space, right?
[00:23:00] Victoria Melnikova: Yes.
[00:23:01] Harjot Gill: So as a founder, like you have to still like make a bet, but like see if something can, you can be on a little bit more stable ground, not just become product that gets disrupted with the next model release or some agent harness can subsume it. That’s always a challenge. Like the B2B is also very interesting space where you can like.
Figure out the complex enterprise workflows, these complex surface areas and bring AI into those, those modes will be there for a longer term versus compared to something that’s easy to disrupt on the consumer side, for example. Right? Because charge GBT and all are like big on consumer side, they just vacuum up all the ideas very quickly.
The B2B, if you really understand like the legal workflows or healthcare workflows go and build in those workflows, there’s a lot of opportunity there.
[00:23:44] Victoria Melnikova: Mm-hmm.
[00:23:45] Harjot Gill: Like code reviews were was also like an enterprise workflow compared to like code generation. We understood that really well, given our experience, and we were able to bring that taste and, and the knowledge very quickly into that.
So that would be my advice. But it’s a great time. Like being in SF right now, this is [00:24:00] kind of the ground zero of a lot of innovation, and that’s why we also moved here. We, I mean, I don’t know whether you remember, we were in the East Bay actually when we started. Oh,
[00:24:07] Victoria Melnikova: yes, yes.
[00:24:07] Harjot Gill: So for the talent access, we had to move here.
Now the, the SF is where all the excitement is.
[00:24:13] Victoria Melnikova: It’s a beautiful choice. You, you did it well. I also wanted to ask, so let’s say we started a company, it’s a dev tool. I don’t know what it is. Let’s say application layer. And now we need to figure out first sales go to market motion. Big questions that all the technical founders face.
And even Martians is an agency for developer tools and we see a lot of demand for go-to-market advice right now because it’s tough, right? Like it’s not obvious. And especially now with the such a high saturation on the market, it’s really hard for people to position their product. Right. What was your experience with CodeRabbit?
Was it crystal clear from day one and you kind of ran a couple of experiments and validated your [00:25:00] idea or. What was the journey? Did you get your design partners on board? Like what was, how was it for coder?
[00:25:06] Harjot Gill: Yeah. It was very non-traditional journey. Like in the other startups you will have design partners.
You’ll generate a lot of content. Mm-hmm. To webinars. Like there are a lot of these like events, like you will go to AWS or something. Those used to be the strategies. 10 years back, the market doesn’t look like that anymore. The way people buy, they discover these products is very different, so. CodeRabbit interest, interestingly, went viral in Japan initially.
[00:25:31] Victoria Melnikova: Wow.
[00:25:31] Harjot Gill: Of all the market. It has nothing to do with us. If you go to this website, zen.dev, ZENN,
[00:25:37] Victoria Melnikova: yes.
[00:25:37] Harjot Gill: You will find codera like 50 plus articles written by end users.
[00:25:41] Victoria Melnikova: Wow.
[00:25:41] Harjot Gill: So that’s also gave us the confidence to actually build a company around it. Mm-hmm. Right. ‘cause what we saw was like a lot of these people were pulling the product versus us having to push.
We didn’t have any design partners, but just the pull in the market was just so strong for something like this. And we were able to iterate based on that once the feedback started [00:26:00] coming in. ‘cause once you have set up the feedback loop, then it’s just about iterating the speed and just going and fixing those things that people are learning into before the competition.
Get, get there. Right. And be that the, the high quality product, enterprise ready product before anyone else. So we were lucky to be in the market as kind of an early mover as well. Mm-hmm. Anyways, though, it wasn’t like we were the only one early mover. We had two or three other companies, which had just started either before us or around the same time, but we were able to iterate very fast.
That was one strength we had. And the way we did it is also like working towards the open source community. Right. And then we did a lot of work with the taste makers, the influencers, especially like on. Twitter and X platform. So a lot of the people were already liking our product and this, we started collaborating with them and they started talking about it.
We did some example YouTube videos like with fire ship and all that. Also put us on a global map, so it’s a mix of influencer marketing, even Google ads. We did like billboards ads [00:27:00] like we did. We are doing like a station takeovers. We did one in New York very recently. Penn State Station. All those strategies are coming into play.
Interestingly, the things that we used to work in my previous startups haven’t yielded a lot of success for us. Like we spent, like I know, hundreds of thousands of dollars on this, like boots and these expos. You get some enterprise customers, but the kind of volume we are seeing through other strategies is very different.
Content is something now we are taking off the ground. It has worked well. In my previous startups. We used to be on like first page of Hacker News a few times in my first startup, second startup. This one, we still have to like see some success. So there’s some areas where are like under investor, we are investing heavily.
[00:27:38] Victoria Melnikova: Yeah.
[00:27:39] Harjot Gill: But there’s some areas where we are running a very consumer style GTM strategy and then that’s working really well.
[00:27:47] Victoria Melnikova: That’s so interesting. Do you think that the cold rabbit popularity in Japan has to do with the name or no?
[00:27:53] Harjot Gill: I don’t think so. It’s just that people over there like usually very forward looking and seen like some [00:28:00] other dev tolling product, even Versal and all talk about if the Japanese market likes a product then it does well internationally as well.
It’s just a market, the way people are more forward looking with these dev tools and, and that feedback really helped us as well on our discord on Twitter.
[00:28:15] Victoria Melnikova: I mean, I love the name, obviously I’m an evil martian, so CodeRabbit is something that I’m like, I love the name. We, we had Iranian joke with Eric on Twitter with Evil Rabbit from Versal, that it’s the three of us can make a party and like evil CodeRabbits, something, you know.
How did the name come about? Is it like, is it just a acute C name or like, what’s the, what’s the deal there?
[00:28:41] Harjot Gill: Yeah, we just wondered something like which people would relate to something because ai, when we started was very new, like back in 2023. A lot of our customers, believe it or not, had not even tried charge GPD.
So this was like their first experience with something like an advanced AI at that point. And for [00:29:00] us, like the bigger battle was like, how do we make this a new habit? Like if you look at developers, they’re very picky. And also the pull requests are a very serious workflow to be part of. Like how do you get the trust of the developer?
There was some sense of friendliness. We wanted to inject, not have something which is too abstract, like anthropomorphic, like that, that like it had to feel relatable. Right. So we went with that name. And also like we were big fans of Datadog, interestingly.
[00:29:24] Victoria Melnikova: Oh yeah.
[00:29:25] Harjot Gill: Right. So we kind of liked what they did with the name and the brand they could work on.
So we kind of built, inspired by that. And, and the reason that I mentioned around like how do we get AI adoption in the early days, so the name helped a lot in terms of adoption, but now maybe it doesn’t matter, like anyone could come up with a different name and, and see success. But in the early days, I feel that it did help.
Even like things like poem, like I know it’s been a very controversial topic with CodeRabbit. Some people like it, a lot of them hate it as well. They can switch it off. But in the early days it did help because people could see the point which was tailored to their [00:30:00] changes. And from that they got the confidence that this AI is actually understanding my changes.
Right. So, and, and, and they could trust the code reviews as well. So early days when we were like creating this market, we had to go through a different set of battles than let’s say someone who’s entering the space now. So we had a lot of education that need to be done.
[00:30:20] Victoria Melnikova: Even though, to your point, I feel like there’s a lot of, I see a lot of animalistic branding still.
Like I feel like it’s still. A very AI thing, like people rely on it a lot and I actually like it because it makes it a little bit more relatable, as you say.
[00:30:34] Harjot Gill: Right. And solid days of personal computing as well. Like if you look at early operating systems, they had used to have a lot of fun Unix.
[00:30:41] Victoria Melnikova: Yes.
[00:30:41] Harjot Gill: You had like and fortune.
And also like if you look at per personal computing, after dark screensavers, like lot of fun stuff used to be there bundled in and the space mature, then things become more clean, nicer. But we are now in the early days of AI where some of this fun stuff, friendly personality does help with that [00:31:00] option.
Mm-hmm. Is what we found. And we have seen that we chat GPD, like G, PT four Oh being more friendly and people were protesting not to take away that bot because GG PT five is like too pragmatic to the point. Yeah. So personality helps in the early days of ai, I don’t know for how long.
[00:31:15] Victoria Melnikova: Mm-hmm.
[00:31:15] Harjot Gill: They do. These products have to be fun, mean after a while it gets like too boring, like and annoying.
Yeah. So we are trying to like balance that out.
[00:31:25] Victoria Melnikova: So if you, if you were to imagine a world in five, 10 years, what’s CodeRabbit like?
[00:31:31] Harjot Gill: Our strength has been more on the enterprise workflows. Mm-hmm. Especially the centralized background agents. So if there’s any company that can win a lot of these background tokens, it’s probably us given the footprint we have with GitHub already.
And now we are also launching new products. There’s a product launch happening tomorrow, which is
[00:31:48] Victoria Melnikova: yes.
[00:31:49] Harjot Gill: When you talk about the bigger vision of CodeRabbit. Because we are going after like the bottlenecks, like if you look at the coding, the inner loop has more or less been [00:32:00] automated, as long as you can express the right intent to these models to accurately describe what you want the model to build, and especially like break it down to smaller agent execution units.
Mm-hmm. These models are doing a really good job. And the other bottleneck is now the validation. So the outer loops one is the intent and the review. They have become the bottleneck. The inner loop, more or less, is becoming more and more automated. Not all the way there. Still human in the loop. That’s why like a lot of companies that went and tried this ticket to pull requests, they were not very successful.
Mm-hmm. The success rate is still low. What works right now is these interactive sessions with ai. That’s where you have cloud code cursor seeing a lot of success. Code reviews is another area that’s working. Then upstream like intent and spectrum and development. I think that’s a big market opportunity right there.
Then there stuff downstream, security is another big one. Mm-hmm. As the models get really good, you want to like find vulnerabilities proactively. So those are some of the [00:33:00] areas and the themes we are working with, like dev environment, downstream, like testing. Because every developer is now either like doing a code review or becoming a QA engineer.
[00:33:08] Victoria Melnikova: Yes.
[00:33:08] Harjot Gill: AI is doing all the coding, right?
[00:33:10] Victoria Melnikova: Yeah.
[00:33:10] Harjot Gill: So it’s for us, like the opportunity lies in like wherever it’s the next bottleneck in the space, go and mm-hmm. Attack it with high quality products.
[00:33:18] Victoria Melnikova: And if we speak about the company itself. What, is it like 500 people, locations all over the world, or what do you think that operationally, what’s the the next big chapter for CodeRabbit?
[00:33:30] Harjot Gill: So right now we are mostly hiring to just keep up with the growth. It’s not like we are hiring because we have the budget. Like right now, the inflow of customers, because most of our customers come inbound. It’s all word of mouth. And we don’t have enough people sometimes to take care of all the support requests coming in or sales queries coming in and deals fall through the cracks.
Yeah. And then people have angry tweets about how bad our support is. So a lot of the times, like our hiring is to just keep up with the growth. Mm-hmm. So yes, I mean, if the demand in the market is [00:34:00] pulling us and in order to meet the SLAs on the support side, sales side, we have to hire Makes sense. And we’ll keep hiring in all those locations even globally.
[00:34:07] Victoria Melnikova: Mm-hmm.
[00:34:07] Harjot Gill: Wherever it makes sense. But ideally, we don’t want to like. Keep growing just for the sake of it. I mean there has to be reason. Even on the product side, we see the same opportunity, like how do we go beyond code reviews to these other initiatives that I talked about and, and if there’s an opportunity there and we find another Blockbuster product, then we can just keep doubling down and grow the teams around those.
[00:34:28] Victoria Melnikova: So when we talk about sync versus a sync culture, kind of like remote or in office, obviously we’re in the office of CodeRabbit and. Me, like I have experienced both. And I think that there are advantages and disadvantages to both. And you mentioned that you wanted to be an SF for the talent source and et cetera.
Is it important for cold rabbit success to be in person in the office sync? Or is it just a nice to have and you know, you could do without it? [00:35:00]
[00:35:00] Harjot Gill: I mean, that’s a great question. I mean, it depends on the teams mm-hmm. That you’re part of. Mm-hmm. Some of the teams at COBIT are still remote. More, but we are more biased towards in person.
My second startup was all remote. We had people in like Romania, Poland as well, in like bunch of locations and it was a challenge, especially in the early days when you’re like working on the product UI and iterating very quickly. It can, the time zone can be very, very challenging. So being under one roof, we are definitely seeing higher velocity.
[00:35:27] Victoria Melnikova: Mm-hmm.
[00:35:27] Harjot Gill: Of ideas and integrations. That said, we also have an office in Bangalore. It’s not like we don’t have any other office out outside sf. So we are also opening up these centers wherever the talent is, because sf, despite all the action, this talent is still scars
[00:35:41] Victoria Melnikova: of course.
[00:35:41] Harjot Gill: Right. And, and you’re competing with all these other labs for the same talent.
At the same time, we also want to get the best talent wherever we can. Mm-hmm. So we are looking at other locations as well. Mm-hmm. Especially if we can build those center of excellence around those products. Right. So that’s the strategy. So it’s kind of like mix of [00:36:00] both worlds as much as possible.
[00:36:02] Victoria Melnikova: So in Bangalore, would you have an office too and where people go and see each other or it’s more of a remote?
[00:36:07] Harjot Gill: It’s an office there as well. 25 to 30. So they also go in person.
[00:36:11] Victoria Melnikova: Yeah,
[00:36:11] Harjot Gill: but there’s still like the time zone that we have to coordinate on the product decisions and the roadmap and so on. Mm-hmm.
[00:36:16] Victoria Melnikova: For
[00:36:16] Harjot Gill: example, a lot of the infrastructure work is done in Bangalore, like a lot of the sandboxes stuff we have done there.
We have a lot of infrastructure we have at Rabbit, which is being done by the team over there, while the team here is core reviews and so on.
[00:36:29] Victoria Melnikova: Yeah. Yeah.
[00:36:30] Harjot Gill: So it’s different swim lanes We have like given ownership to different locations.
[00:36:35] Victoria Melnikova: Yeah. Very nice.
[00:36:36] Harjot Gill: But some teams are remote, like a lot of our marketing happens to be mm-hmm.
Remote. Mm-hmm. Our head of content, for example, is based out of Canada and so on. Yeah.
[00:36:43] Victoria Melnikova: Honestly, the time kind of flew, but we are arriving at my final question, which is always the same. It’s called warm phases question. And it goes like this. What makes you feel great about what you’re doing today?
[00:36:56] Harjot Gill: Like what I love about this job right now is the users who love the [00:37:00] product.
That’s what keeps us going in a way, like we do feel that we are making a genuine difference in the way. Mm-hmm. People are delivering software and doing their jobs. A lot of people are thankful for the issues we have prevented. That’s very, very encouraging. So this is a product that is actually moving the needle, making a real world impact, and it’s a lot of responsibility.
We feel that way, so we feel great at the same time, there’s a sense of responsibility you get in how to make it even better and how to even like build more products that can save, save them time in, in, in other activities they’re doing.
[00:37:32] Victoria Melnikova: And finally, I mean, even though we’re at your office, I want to provide you with the stage to invite people to try CodeRabbit.
How can they find it? Where should they start?
[00:37:43] Harjot Gill: Yeah, they can always go to our website code abbit ai, and it’s just two clicks to sign up connecting to GitHub GitLab. They could also find us on VS. Code Marketplace. Mm-hmm. So they can try it locally in the VS code or the CLI environments and then bring it to their teams in GitHub.
In fact, code Abbit is free for individual users. [00:38:00] On, especially if they’re using BS code in the CLA form factor.
[00:38:04] Victoria Melnikova: Perfect. Thank you so much Raja. It was a pleasure.
[00:38:07] Harjot Gill: Thanks Victoria.
[00:38:09] Victoria Melnikova: Thank you for catching yet another episode of Deaf Propulsion Labs. We at Evil Martians transform growth stage startups into unicorns, build developer tools, and create open source products.
If you, a developer tool needs help with product design development or SRE. Visit evil martians.com/dev tools. See you in the next.
