00:54:50 · Varun Badhwar
And I would say the person in New York probably had way higher of a more experienced background and became way more well referred and reputable, et cetera, et cetera. The person on the west was just scrappy. And it turns out nine months later, the person on the west had closed five deals, the person on the east had closed zero deals. And I swear, if I didn't have the person on the west coast, I would have believed that Redlock, we had built the wrong product. The reality was we had not built the wrong product, we had built the right product. We actually were even targeting the right kind of accounts, but the individual was going through some life issues, personal life issues, and other things we didn't know at the time, that was affecting their ability to execute and perform. And that's very hard to tell. So I think come like tying all of that together today to uh endor, and you kind of asking about like what's working, what's not, I think you you have to when you're looking for talent, you need to find people that are you finding them at the right point in their career? Are they ready and and willing and understanding of what it takes to be in a startup? Because they could be extremely successful where they are, but the fit of your company, your stage, and your needs matters way more than you think. Because a lot of times we want that brand, right? I want to be able to go to an investor and say, look, I have five engineers from Meta. But are those five engineers from Meta the right background and DNA of what you need to go find product market fit on a zero-to-one product?
00:56:31 · Siddhartha Ahluwalia, Varun Badhwar
[00:56:31] S1: And what do you say in Endor, finding product market fit is as hard as Redlock? Or has it become easier also as like a third-time founder? [00:56:40] S0: I wouldn't say it's easier. I think it's also not a fair comparison because um red lock was a market creation moment. We were creating a new category of products to solve a new pain. At Endor, we have been creating a new architecture and paradigm, an entirely new way of solving an age-old problem. It's almost like we at Redlock, we were inventing cars. Cars didn't exist. At Endor, we are moving from gasoline to electric cars. Like we've changed the entire drivetrain of what a car looks, what is possible with a car, and introduce those self-driving capabilities that you can actually believe are safe and can work and scale that didn't exist. So I think there's a completely different structure of how to compare a market creation versus a market disruption. Um, so that's kind of why I don't think it's a fair comparison. [00:57:44] S1: Got but has it been easier or more difficult? What would you say?
00:57:47 · Varun Badhwar
[00:57:47] S0: It's been different. And I say that because when when you are creating a category, there's no incumbency. So whatever you define either solves the problem or doesn't. When you're disrupting an existing category that's been around for 20 years, you need to build the differentiation, but you've got to build the long tail of every other feature function that existing products have and support and integrations, because that's what a customer has been using for many years. So they need all of that that they use, and they need a significant order of magnitude differentiation to go through the work and pain of removing an incumbent tool and swapping it out. The thing that then shifted and put this into hyperdrive for Endor was when AI coding came along. Because until AI coding came along, it was like, look, you've had this problem, you've tolerated it, now you need to change your way so you can get a better experience. The AI coding agent disrupted entirely what a workflow looks like, what an agentic STLC, how you create software. It completely disrupted this whole idea of, you know, today we're identifying 16 times more vulnerabilities than we can fix. That gap has widened more in the last year than it has in the last 10 years. That pain didn't exist for the last 10 years. So I would say the hyperdrive is coming from AI coding agents are now saying, well, not only is this a disruption of an existing category, but it's an entire rewrite of the entire workflow of how you do the moving forward.
00:59:26 · Siddhartha Ahluwalia, Varun Badhwar
[00:59:26] S1: So hypothetically, if you imagine at a company, a tech forward company, if 100x more code is getting written, are the vulnerabilities also increasing by 100x? [00:59:39] S0: Easily, yes. Because I think the linear formula would say that. It's not just you're creating more software, you're also creating them at a more faster pace. The other challenge, I was with a CIO of a very large entertainment company. And he said, Varun, look, my problem is not just I have citizen developers. My finance team is building a forecasting app. And we happened to go analyze that code, we found a security bug. We emailed the individual who is writing that code, and we said, Here, could you please fix this vulnerability? Do you want to guess what the response of that individual was to the security team? [01:00:25] S1: I didn't create it. The agent created it. So please ask me.
01:00:28 · Varun Badhwar
[01:00:28] S0: Actually, even more fundamental, which is what's a vulnerability? Like now you're talking about securing an ecosystem of code that is being generated 10 times faster with more security problems, but also the dynamics of the individuals you're working with, is you're going back to their baseline. So at that point, to your, I basically where you're going with your idea is security just needs to be autonomous. Security just needs to be handled for the user, not being something that a user needs to think about and be trained about. And I think that opportunity exists. Think about this. For the last 20 years, for people who are on this podcast that are listening, that are software engineers. Every year in your company you go through an annual security training. They teach you how to write code. But then there are 20,000 of you in the company. Do we realistically believe that 20,000 people will remember and follow all the instructions on how to do things manually? Unlikely. But with agents, you can actually give agents consistent instructions to follow the same parameters if you can infuse that intelligence to them. So like at Endor, our product infuses that intelligence into cloud code, into cursor, into codecs. And just make sure when they are creating these loops of code, the security intelligence is fused in and they're instructed to fix the problems they're introducing right at the source. And I think agents are far more capable to do that consistently than humans can. I think that's the we've been talking a lot about like the risks of AI. But that's the boon of AI. We can now solve these problems that have been unsolved for 20 years, despite more volume, despite reduction in time we have to fix these differently. And that's what I'm most excited about.
01:02:13 · Siddhartha Ahluwalia, Varun Badhwar
[01:02:13] S1: So uh at Endor, when the code is getting reviewed as it's getting written, is it completely autonomous? [01:02:24] S0: It can be. Some of our customers are in the everything is fairly autonomous unless it's a known large disruptive change, you gotta bring a human in the loop. There are others that are still using our context to create gear tickets and not be in the developer workflow. This goes back to my uh example of meet customers where they are and then take them to your promised land and dreamline. If we had designed the product to just be autonomous, what would we do with all the customers that are not ready? And so I think it becomes really important to think about designing your product for the masses. And that's kind of where one of the common fallacies a lot of startups in Silicon Valley have is they'll talk to their friends in Silicon Valley, understand the problem, build a product, and be like, oh, well, nobody else is really thinking of it this way. And so I always tell people when they're ideating, don't be in the bubble. Get out of the bubble and go talk to you know the company that has a 40-year-old code base or has 100,000 employees worldwide that is regulated entirely differently than how Silicon Valley operates. [01:03:52] S1: But but your agents are always watching the AI coding agents, whatever they be. Yes.